GCAGA: A Gini Coefficient-Based Optimization Strategy for Computation Offloading in Multi-User-Multi-Edge MEC System

To support the explosive growth of Information and Communications Technology(ICT),Mobile Edge Comput-ing(MEC)provides users with low latency and high bandwidth service by offloading computational tasks to the network’s edge.However,resource-constrained mobile devices still suffer from a capacity mismatch when faced with latency-sensitive and compute-intensive emerging applications.To address the difficulty of running computationally intensive applications on resource-constrained clients,a model of the computation offloading problem in a network consisting of multiple mobile users and edge cloud servers is studied in this paper.Then a user benefit function EoU(Experience of Users)is proposed jointly considering energy consumption and time delay.The EoU maximization problem is decomposed into two steps,i.e.,resource allocation and offloading decision.The offloading decision is usually given by heuristic algorithms which are often faced with the challenge of slow convergence and poor stability.Thus,a combined offloading algorithm,i.e.,a Gini coefficient-based adaptive genetic algorithm(GCAGA),is proposed to alleviate the dilemma.The proposed algorithm optimizes the offloading decision by maximizing EoU and accelerates the convergence with the Gini coefficient.The simulation compares the proposed algorithm with the genetic algorithm(GA)and adaptive genetic algorithm(AGA).Experiment results show that the Gini coefficient and the adaptive heuristic operators can accelerate the convergence speed,and the proposed algorithm performs better in terms of convergence while obtaining higher EoU.The simulation code of the proposed algorithm is available:https://github.com/Grox888/Mobile_Edge_Computing/tree/GCAGA.

Gini Coefficient-based Task Allocation for Multi-robot Systems With Limited Energy Resources

Nowadays, robots generally have a variety of capabilities, which often form a coalition replacing human to work in dangerous environment, such as rescue, exploration, etc. In these operating conditions, the energy supply of robots usually cannot be guaranteed. If the energy resources of some robots are consumed too fast, the number of the future tasks of the coalition will be affected. This paper will develop a novel task allocation method based on Gini coefficient to make full use of limited energy resources of multi-robot system to maximize the number of tasks. At the same time, considering resources consumption,we incorporate the market-based allocation mechanism into our Gini coefficient-based method and propose a hybrid method,which can flexibly optimize the task completion number and the resource consumption according to the application contexts.Experiments show that the multi-robot system with limited energy resources can accomplish more tasks by the proposed Gini coefficient-based method, and the hybrid method can be dynamically adaptive to changes of the work environment and realize the dual optimization goals.

Estimating Gini Coefficient Based on Hurun Report and Poverty Line

Based on the review of various methods of estimating Gini coefficient, the paper applies a quintile rule to estimate Gini coefficient of rural areas, urban areas and the whole country using the grouped income data of urban and rural residents. Besides, the paper uses the curve-fitting method to roughly estimate Gini coefficient from eye-catching Hurun Rich List and the latest poverty line. The result shows that the estimation of Gini coefficient using quintile rule is small for both urban and rural area, while the value of the whole country is obviously larger, which is above the warning line of 0.4. It is indicated that the wealth gap mainly comes from the gap between urban and rural areas. On the other hand, the estimation of Gini coefficient using curve-fitting method is as large as more than 0.7, which implies that the wealth gap is?highlighted from the analysis of the lowest and highest part of the wealth distribution. All in all, China’s current gap between the poor and the rich is serious. The reform of the income distribution needs to speed up to ensure social harmony and stability.

Fair hierarchical clustering of substations based on Gini coefficient

For the load modeling of a large power grid,the large number of substations covered by it must be segregated into several categories and,thereafter,a load model built for each type.To address the problem of skewed clustering tree in the classical hierarchical clustering method used for categorizing substations,a fair hierarchical clustering method is proposed in this paper.First,the fairness index is defined based on the Gini coefficient.Thereafter,a hierarchical clustering method is proposed based on the fairness index.Finally,the clustering results are evaluated using the contour coefficient and the t-SNE two-dimensional plane map.The substations clustering example of a real large power grid considered in this paper illustrates that the proposed fair hierarchical clustering method can effectively address the problem of the skewed clustering tree with high accuracy.

高放废物缓冲材料的均匀性分析–基于密度比模型下的Gini系数

提出用密度比模型估计缓冲材料含水率和干密度的Gini系数,并在此基础上进行假设检验,以解决核安全领域中如何科学分析缓冲材料均匀性的难点.对假设检验所涉及的渐近理论进行了探讨.提出在进行Wald-型检验的同时可借助自助法来提高检验功效.基于上述方法对覆膜储存法试验所得的实际数据进行相应的估计和假设检验,所得的结果验证了覆膜储存法对缓冲材料均匀性的保护是有效的.

China Is to Maintain GINI Coefficient within 0.4% by 2020

Editorial note Income gap has been considered one of the most potent threats to China’s society and economy in the future.This paper finds that China’s residential income gap has exceeded the reasonable bound but still falls within the tolerable range.Following an analysis of the causes of widening income gap,the authors also attempt to lay out an institutional arrangement framework aimed at achieving fair and equitable distribution from the three respects of starting point,process and result.

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。

Developing a novel quantitative parameter for characterizing spatial distribution of fish following exposure to chemicals and wastewater:Behavioral Gini coefficient

While the spatial distribution pattern of fish is increasingly used for toxicological test o chemicals or wastewater,no ideal parameter is available for quantitative assessment of spa tial distribution,especially uneven distribution with multiple hotspots.Here,to develop a quantitative assessment parameter for spatial distribution,the zebrafish were exposed to ethanol,pentylenetetrazole(PTZ),paraquat dichloride(paraquat)and wastewater,followed by a behavioral test in a narrow tank.Behavioral data was acquired and analyzed by id Tracker and MATLAB.By comparing the effects of all treatments on behavior parameters we confirmed that the spatial distribution was more easily altered rather than general loco motor parameters,e.g.0.7-70 mg/L PTZ and 5-20 mg/L paraquat being effective for altering spatial distribution but having little effects on general locomotor parameters.Based on the heatmap,i.e.,the cumulative proportion of grids and that of frequency in grids,we calcu lated the behavioral Gini coefficient(G_(b))for quantitative assessment of fish spatial distri bution.The Gini coefficient ranged from zero to 1,with larger values meaning poorer even ness of spatial distribution.Of note,G_(b)showed smaller coefficient of variations(CV)with3%-19%between replicate tanks in all treatments than the highest frequency(4%-79%),dis playing well robustness.Especially,G_(b)addressed the challenge of the complicated heatmap with multiple hotspots.Overall,the behavioral Gini coefficient we established is an idea parameter to quantitatively assess spatial distribution of fish shoal,which is expected to be applied in toxicity testing for chemicals and wastewater and automatic quality monitoring for surface water and aquaculture water.

中国数字经济发展水平的地区差异、空间集聚与状态转移

文章基于TOPSIS法,通过CRITIC权与灰色关联理论构建CRITIC权灰色关联TOPSIS法,并将其在空间与时间上应用两次,从而可对面板数据进行短期评价。根据新评价法测算2015—2020年中国31个省份的数字经济发展水平并展开分析,结果显示:中国数字经济发展水平地区差异显著,主要取决于三大地区间的差异,且有扩大趋势;北京、上海稳居前2名,浙江、广东、福建、天津、江苏稳居第3至第7名;贵州、青海数字经济发展进步较大,东北三省排名退步显著;省域数字经济发展水平状态转移较难,跨级状态转移基本不会发生,较低水平状态为贫困陷阱,陷于其中的省份很难靠自身得到提升;中国数字经济发展水平存在空间集聚现象,基于配对t检验的结果表明,数字经济可以在一定程度上打破地理限制。

中国共同富裕水平测度及区域差异分析

文章构建了中国共同富裕水平测度指标体系,基于中国31个省份2013—2021年的相关数据,通过熵权法进行赋权,运用全局及局部Moran’s I、Dagum基尼系数分析中国共同富裕水平整体差异以及区域差异,依托Dagum基尼系数分解分析其差异来源及大小。结果表明:中国共同富裕水平总体上呈上升趋势;基于空间相关性的角度,中国共同富裕水平全局空间分布存在聚集性,2017年以后,各省份共同富裕水平存在的空间相关性有增强趋势,大部分省份之间存在较强的局部空间自相关性,总体上处于相对稳定的发展态势;通过对区域差异来源及大小的比较发现,区域间差异是影响中国共同富裕水平最主要的因素,区域之间以及区域内部共同富裕水平的差异呈逐渐缩小趋势,整体共同富裕水平朝着均衡方向发展。

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。

环境规制、数据要素配置水平与产业结构调整

文章基于数字经济、绿色经济发展深刻影响产业结构转型升级进程这一背景,首先在理论分析的基础上构建了数据要素配置水平综合评价指标体系;然后采用Dagum基尼系数对数据要素配置水平的空间差异及主要来源进行分解测算;最后,基于2012—2019年省级面板数据探讨了环境规制的结构调整红利及数据要素有效配置的渠道效应。研究结果显示,我国数据要素配置水平总体空间差异明显,且区域间差异为主要来源,区域内差异次之。环境规制对产业结构升级存在先促进后抑制的“倒U”型影响,数据要素配置也有显著促进作用。动态边际效应结果显示,在研究期内环境规制所带来的产业结构“调整红利”正在逐渐弱化,数据要素优化配置可充当环境规制促进产业结构升级的有效路径,且从子维度来看,数据传播共享的渠道效应最为显著。数据要素配置的网络外部性特征对环境规制和产业结构优化的调节作用在不同地区所呈现的阶段性特征不同。

粮食功能区视角下农业高质量发展水平及区域差异研究

基于2016—2020年省级农业发展数据,综合运用改进后的熵值法、Dagum基尼系数等方法,测算了全国及粮食功能区农业高质量发展水平及差异程度,并进一步从一级指标入手,分析了引起区域差异产生和波动的原因。结果表明:(1)三大粮食功能区的农业高质量发展水平均保持上升趋势,按水平由大到小依次为“主销区、主产区、平衡区”。(2)三大粮食功能区存在区域差异,区域间的差异是总体差异的主要来源,区域内差异也出现不同程度的变动。(3)主销区内部差异波动与产业升级指标相关,主产区内部差异波动主要受产出高效和产业升级指标影响,平衡区内部差异波动源于产业升级指标中的追赶效应。(4)区域间差异主要源自产业升级指标,成果共享指标也起到部分影响作用,三大区域各具发展短板。因此,为提升我国农业高质量发展均衡性,应坚持“因地制宜”原则,以水平最低的平衡区为发力点,以产业升级指标为抓手,以各区域发展短板为突破,采取更具针对性的发展措施。

中国粮食种植业碳效应时空演化及碳排放公平性

农业低碳转型背景下,准确把握粮食种植业碳效应时空演化及碳排放公平性特征对实现地区生态正义具有重要意义。基于2000—2021年省域面板数据,采用碳排放因子法测算中国30个省区的粮食种植业碳效应,利用核密度估计方法探析时空演化,运用Dagum基尼系数法刻画并解构全国粮食种植业碳排放公平性。研究表明:(1)从时空特征看,粮食种植业碳效应呈现波动上升的净碳汇特征,具体表现为“东强西弱,北高南低”的空间格局,且伴随明显的“马太效应”。在碳效应结构上,秸秆燃烧与玉米种植分别是粮食种植业最主要的碳源与碳汇。(2)从演化趋势来看,全国粮食种植业碳效应的非均衡性呈扩大趋势;在三大主粮中,水稻碳效应非均衡性有所减弱,小麦与玉米碳效应非均衡性均持续上升。(3)从碳排放公平性来看,区域间碳排放差异已成为影响公平性的最主要因素,基尼系数呈“快速上升-波动震荡-缓慢回落”特征,全国粮食种植业碳排放始终处于较公平区间,整体公平性呈改善态势;在三大主粮中,水稻碳排放公平性最低,玉米碳排放公平性最高。最后,提出了采取差异化固碳减排策略、构建低碳发展跨区协作机制、完善碳排放责任分摊机制、探索粮食碳汇交易试点等建议,以期推动我国粮食种植业实现低碳转型发展。

易地扶贫搬迁农户生态系统服务收益不平等的测度和分解研究

生态系统服务与人类福祉和社会经济可持续发展密切相关。在乡村振兴背景下,生态系统服务收益不平等程度的降低有助于提升农村居民对环境保护的关切,促进农村地区生态环境改善,推动农村经济、社会和环境的协调发展。基于2021年陕西易地扶贫搬迁入户调研数据,测度和分解了搬迁农户生态系统服务收益不平等。首先,测度农户在搬迁前后生态系统服务收益不平等程度;其次,基于静态视角利用基尼系数分解生态系统服务收益构成对其不平等的贡献度;最后,基于动态视角利用夏普里分解法量化了生态系统服务收益影响因素对其不平等的贡献度。结果表明,生态系统服务总收益不平等和调节服务收益不平等在搬迁后有所降低,供给服务不平等和文化服务不平等在搬迁后均提高;调节服务收益、供给服务收益、文化服务收益对总收益不平等贡献度依次递减,但与其他两种收益不同,调节服务收益增加会使总收益不平等程度降低;相同影响因素对生态系统服务总收益不平等和各分项收益不平等贡献度具有差异,政策因素是影响因素中造成总收益不平等及分项收益不平等的主要原因。本研究为基于不平等视角探究生态系统服务提供路径支持和方法借鉴,也为新时期易地扶贫搬迁地区生态保护政策的制定和实施提供启示。

基于基尼系数分解的城乡公共交通不平等测度:以浙江省海宁市为例

探明城乡公共交通不平等来源及其变化特征对缩小城乡差距有重要意义,以浙江省海宁市为例,将站点可达性作为公共交通服务指标,以交通小区作为分析单元计算公共交通可达性,分别计算2011—2020年研究区域总体、城区、农村及城乡间的基尼系数,将总体基尼系数按城区和农村两个子群进行分解,分析城乡公共交通不平等来源及其演变特征。结果发现:总体基尼系数为0.7204~0.7736,城区基尼系数为0.5718~0.6058,农村基尼系数为0.5955~0.6390,城乡间基尼系数为0.8131~0.8710,研究区域公共交通严重不平等,城乡间不平等程度最大;2011—2020年间总体、城区、农村和城乡间的基尼系数分别下降了5.62%、6.88%、5.21%和6.65%,公共交通不平等不断改善;城乡间不平等对总体不平等的贡献率为63.03%~67.58%,是总体不平等的主要来源。研究表明,基尼系数分解能有效测度城乡公共交通不平等来源,缩小城乡间不平等是城乡客运均等化发展的重要任务。

中国数字普惠金融区域协同发展机制与路径研究——基于八大综合经济区视角

在测度中国数字普惠金融发展水平基础上,采用Dagum基尼系数、方差分解和地理探测器方法从空间协同、结构协同及外在驱动因素三个方面考察我国数字普惠金融协同发展状况与协同机制,并据此探究我国数字普惠金融协同发展路径。研究发现:样本期间全国整体及八大综合经济区数字普惠金融水平均呈上升态势,但地区间分异显著;区域间差异是阻碍数字普惠金融协同发展的主要空间来源;对于全国整体来说,覆盖广度差异是数字普惠金融发展不协同的主要结构来源,而在东部沿海、南部沿海、黄河中游等地区,使用深度差异超过覆盖广度差异成为影响区域内数字普惠金融发展不协同的主要结构来源;不论是在全国整体还是八大综合经济区,降低互联网覆盖差异和经济发展水平差异都是驱动数字普惠金融协同发展的主要因素,且每两对因素组合都会加强各自对数字普惠金融协同发展的影响。本文基于八大综合经济区视角,揭示了我国数字普惠金融发展的空间协同、结构协同和外在驱动机制,为探寻数字普惠金融协同发展路径提供有益借鉴。

基尼系数测度贫富差距的一种改进方法

基尼系数是测度贫富差距的重要指标,但是洛伦兹曲线的构造使得基尼系数存在结构性局限,即代表着不同的贫富差距情况的两条洛伦兹曲线可能对应着同一个基尼系数,仅凭基尼系数无法反映贫富差距的结构特征。文章提出将洛伦兹曲线上切线斜率为1的点叫做平均增长点,每条洛伦兹曲线有且仅有一个平均增长点,洛伦兹曲线切线斜率具有单调性,可以通过引入平均增长点,与基尼系数共同测度贫富差距,突破单纯依靠基尼系数测度贫富差距的结构性局限。