基于邻域K-shell分布的关键节点识别方法

复杂网络中关键节点的精准识别对于网络结构稳定和信息传播起着至关重要的作用。传统K-shell方法仅通过节点在网络中所处位置对节点的重要性进行评估,导致区分度不高。基于此,综合考虑了节点的全局信息和局部信息对节点重要性的影响,提出一种基于邻域K-shell分布的关键节点识别方法。该方法通过节点邻域Ks值定义节点的熵,从而反映邻居节点的K-shell分布特征。通过11个网络数据集上的仿真实验,验证了所提方法能够更准确地识别并区分复杂网络中的关键节点。

改进K-shell算法的城市道路网关键交叉口识别

交叉口重要性不仅与自身属性相关,还受相邻路段属性的影响,针对城市道路网中关键交叉口识别方法准确率不足的问题,提出一种考虑城市道路网特性的改进K-shell算法。即在传统K-shell算法基础上,综合考虑交叉口及其相邻路段的结构特性与交通特性,提出交叉口重要度的概念,利用CRITIC法确定交叉口重要度中相关指标的权重系数,对城市道路网中的交叉口进行重要性排序。以哈尔滨市二环内道路网为例,构建级联失效模型,分析随着失效交叉口比例的增加,不同排序方法下的网络效率、网络最大连通子图比率、故障节点比率的波动情况,结果表明,改进K-shell算法能够更加有效地识别城市道路网关键交叉口。

Grindability Evaluation of Ultrasonic Assisted Grinding of Silicon Nitride Ceramic Using Minimum Quantity Lubrication Based SiO_(2)Nanofluid

Minimum quantity Lubrication(MQL)is a sustainable lubrication system that is famous in many machining systems.It involve the spray of an infinitesimal amount of mist-like lubricants during machining processes.The MQL system is affirmed to exhibit an excellent machining performance,and it is highly economical.The nanofluids are understood to exhibit excellent lubricity and heat evacuation capability,compared to pure oil-based MQL system.Studies have shown that the surface quality and amount of energy expended in the grinding operations can be reduced considerably due to the positive effect of these nanofluids.This work presents an experimental study on the tribological performance of SiO_(2)nanofluid during grinding of Si_(3)N_(4)ceramic.The effect different grinding modes and lubrication systems during the grinding operation was also analyzed.Different concentrations of the SiO_(2)nanofluid was manufactured using canola,corn and sunflower oils.The quantitative evaluation of the grinding process was done based on the amount of grinding forces,specific grinding energy,frictional coefficient,and surface integrity.It was found that the canola oil exhibits optimal lubrication performance compared to corn oil,sunflower oil,and traditional lubrication systems.Additionally,the introduction of ultrasonic vibrations with the SiO_(2)nanofluid in MQL system was found to reduce the specific grinding energy,normal grinding forces,tangential grinding forces,and surface roughness by 65%,57%,65%,and 18%respectively.Finally,regression analysis was used to obtain an optimum parameter combinations.The observations from this work will aid the smooth transition towards ecofriendly and sustainable machining of engineering ceramics.

The impact of the Rural Minimum Living Standard Guarantee(Rural Dibao)Program on child nutrition outcomes

The Rural Minimum Living Standard Guarantee(Rural Dibao)is an important unconditional cash transfer program to alleviate poverty in rural China.Despite the importance of children’s nutrition in breaking poverty cycles,little is known about the impact of Rural Dibao on child nutrition outcomes.Using China Family Panel Studies(CFPS),this paper examines the effects of Rural Dibao on child nutrition outcomes and investigates potential pathways and heterogeneous effects.We exploit propensity score matching and difference-in-differences techniques to evaluate the effects of the Rural Dibao program on child nutrition outcomes.Our results suggest that Rural Dibao significantly impacts the nutrition outcomes of children up to 15 years of age.Specifically,our results suggest that Rural Dibao improves child height-to-age z-scores by 1.05 standard deviations and lowers the probability of stunting by 11.9 percentage points.Additional analyses suggest that increased protein intake is the main pathway through which Rural Dibao participation contributes to better nutrition outcomes.We also find that the effect of the program is more pronounced among girls,children who are non-left-behind or live with highly educated mothers,and those from low-income families and poor areas.Our findings suggest that Rural Dibao participation helps improve child nutrition outcomes through improving diet quality.

Comparison of the Minimum Bounding Rectangle and Minimum Circumscribed Ellipse of Rain Cells from TRMM

Based on the TRMM dataset, this paper compares the applicability of the improved MCE(minimum circumscribed ellipse), MBR(minimum bounding rectangle), and DIA(direct indexing area) methods for rain cell fitting. These three methods can reflect the geometric characteristics of clouds and apply geometric parameters to estimate the real dimensions of rain cells. The MCE method shows a major advantage in identifying the circumference of rain cells. The circumference of rain cells identified by MCE in most samples is smaller than that identified by DIA and MBR, and more similar to the observed rain cells. The area of rain cells identified by MBR is relatively robust. For rain cells composed of many pixels(N> 20), the overall performance is better than that of MCE, but the contribution of MBR to the best identification results,which have the shortest circumference and the smallest area, is less than that of MCE. The DIA method is best suited to small rain cells with a circumference of less than 100 km and an area of less than 120 km^(2), but the overall performance is mediocre. The MCE method tends to achieve the highest success at any angle, whereas there are fewer “best identification”results from DIA or MBR and more of the worst ones in the along-track direction and cross-track direction. Through this comprehensive comparison, we conclude that MCE can obtain the best fitting results with the shortest circumference and the smallest area on behalf of the high filling effect for all sizes of rain cells.

基于K-shell的加权网络节点影响力研究方法

针对现有关键节点识别方法在准确性和分辨率上的局限性,提出了一种改进的K-shell排序方法,在传统K-shell分解的基础上,结合节点度数、邻居节点影响力和边权重,引入信息熵理论,细化同一K-shell层内节点的相对重要性。实验结果表明:该方法显著提升了排序的准确性和单调性,能够更有效地区分同一K-shell层内的节点重要性,准确识别出对网络结构影响较大的关键节点。该算法从多个维度考虑影响关键节点识别重要性的因素,在准确性和分辨率方面有显著的提升,对网络匿名隐私保护中的关键节点挖掘具有重要意义。

基于K-Shell2重要度传导的作战体系节点评估方法

为提高联合作战体系中关键节点判断的准确性,提出了基于K-Shell2重要度传导的作战体系节点评估方法。以K-Shell2核度算法为基础,根据重要度传导原则和有效传导原则建立评估算法模型,采用重要度迭代传导方式获得节点最终重要度。通过实验对比分析,所提方法能够准确划分节点重要性层次,有效提高了同层节点的分辨率,可为联合火力打击目标选取决策提供重要依据。

Quantum algorithm for minimum dominating set problem with circuit design

Using quantum algorithms to solve various problems has attracted widespread attention with the development of quantum computing.Researchers are particularly interested in using the acceleration properties of quantum algorithms to solve NP-complete problems.This paper focuses on the well-known NP-complete problem of finding the minimum dominating set in undirected graphs.To expedite the search process,a quantum algorithm employing Grover’s search is proposed.However,a challenge arises from the unknown number of solutions for the minimum dominating set,rendering direct usage of original Grover’s search impossible.Thus,a swap test method is introduced to ascertain the number of iterations required.The oracle,diffusion operators,and swap test are designed with achievable quantum gates.The query complexity is O(1.414^(n))and the space complexity is O(n).To validate the proposed approach,qiskit software package is employed to simulate the quantum circuit,yielding the anticipated results.

April-September minimum temperature reconstruction based on Sabina tibetica ring-width chronology in the central eastern Tibetan Plateau,China

Minimum temperatures have remarkable impacts on tree growth at high-elevation sites on the Tibetan Plateau,but the shortage of long-term and high-resolution paleoclimate records inhibits understanding of recent minimum temperature anomalies.In this study,a warm season(April–September)reconstruction is presented for the past 467 years(1550–2016)based on Sabina tibetica ring-width chronology on the Lianbaoyeze Mountain of the central eastern Tibetan Plateau.Eight warm periods and eight cold periods were identified.Long-term minimum temperature variations revealed a high degree of coherence with nearby reconstructions.Spatial correlations between our reconstruction and global sea surface temperatures suggest that warm season minimum temperature anomalies in the central eastern Tibetan Plateau were strongly influenced by large-scale ocean atmospheric circulations,such as the El Ni?o-Southern Oscillation and the Atlantic Multidecadal Oscillation.

Power Allocation for SE Maximization in Uplink Massive MIMO System Under Minimum Rate Constraint

In this paper,we optimize the spectrum efficiency(SE)of uplink massive multiple-input multiple-output(MIMO)system with imperfect channel state information(CSI)over Rayleigh fading channel.The SE optimization problem is formulated under the constraints of maximum power and minimum rate of each user.Then,we develop a near-optimal power allocation(PA)scheme by using the successive convex approximation(SCA)method,Lagrange multiplier method,and block coordinate descent(BCD)method,and it can obtain almost the same SE as the benchmark scheme with lower complexity.Since this scheme needs three-layer iteration,a suboptimal PA scheme is developed to further reduce the complexity,where the characteristic of massive MIMO(i.e.,numerous receive antennas)is utilized for convex reformulation,and the rate constraint is converted to linear constraints.This suboptimal scheme only needs single-layer iteration,thus has lower complexity than the near-optimal scheme.Finally,we joint design the pilot power and data power to further improve the performance,and propose an two-stage algorithm to obtain joint PA.Simulation results verify the effectiveness of the proposed schemes,and superior SE performance is achieved.

Dynamic Event-Triggered Consensus Control for Input Constrained Multi-Agent Systems With a Designable Minimum Inter-Event Time

This paper investigates the consensus control of multi-agent systems(MASs) with constrained input using the dynamic event-triggered mechanism(ETM).Consider the MASs with small-scale networks where a centralized dynamic ETM with global information of the MASs is first designed.Then,a distributed dynamic ETM which only uses local information is developed for the MASs with large-scale networks.It is shown that the semi-global consensus of the MASs can be achieved by the designed bounded control protocol where the Zeno phenomenon is eliminated by a designable minimum inter-event time.In addition,it is easier to find a trade-off between the convergence rate and the minimum inter-event time by an adjustable parameter.Furthermore,the results are extended to regional consensus of the MASs with the bounded control protocol.Numerical simulations show the effectiveness of the proposed approach.

Anomaly-Resistant Decentralized State Estimation Under Minimum Error Entropy With Fiducial Points for Wide-Area Power Systems

This paper investigates the anomaly-resistant decentralized state estimation(SE) problem for a class of wide-area power systems which are divided into several non-overlapping areas connected through transmission lines. Two classes of measurements(i.e., local measurements and edge measurements) are obtained, respectively, from the individual area and the transmission lines. A decentralized state estimator, whose performance is resistant against measurement with anomalies, is designed based on the minimum error entropy with fiducial points(MEEF) criterion. Specifically, 1) An augmented model, which incorporates the local prediction and local measurement, is developed by resorting to the unscented transformation approach and the statistical linearization approach;2) Using the augmented model, an MEEF-based cost function is designed that reflects the local prediction errors of the state and the measurement;and 3) The local estimate is first obtained by minimizing the MEEF-based cost function through a fixed-point iteration and then updated by using the edge measuring information. Finally, simulation experiments with three scenarios are carried out on the IEEE 14-bus system to illustrate the validity of the proposed anomaly-resistant decentralized SE scheme.

The Study of Root Subspace Decomposition between Characteristic Polynomials and Minimum Polynomial

Let Abe the linear transformation on the linear space V in the field P, Vλibe the root subspace corresponding to the characteristic polynomial of the eigenvalue λi, and Wλibe the root subspace corresponding to the minimum polynomial of λi. Consider the problem of whether Vλiand Wλiare equal under the condition that the characteristic polynomial of Ahas the same eigenvalue as the minimum polynomial (see Theorem 1, 2). This article uses the method of mutual inclusion to prove that Vλi=Wλi. Compared to previous studies and proofs, the results of this research can be directly cited in related works. For instance, they can be directly cited in Daoji Meng’s book “Introduction to Differential Geometry.”

Macroscopic Traversable Wormholes: Minimum Requirements

While wormholes are just as good a prediction of Einstein’s theory as black holes, they are subject to severe restrictions from quantum field theory. To allow for the possibility of interstellar travel, a macroscopic wormhole would need to maintain sufficiently low radial tidal forces. It is proposed in this paper that the assumption of zero tidal forces, i.e., the limiting case, is sufficient for overcoming the restrictions from quantum field theory. The feasibility of this approach is subsequently discussed by 1) introducing the additional conditions needed to ensure that the radial tidal forces can indeed be sufficiently low and 2) by viewing traversable wormholes as emergent phenomena, thereby increasing the likelihood of their existence.

基于K-shell及动力学模型的SPN关键节点识别算法

SPN网络采用切片分组组网策略进行网络传输,由于其高效的业务承载能力,SPN网络已成为各种切片业务综合性传输承载网络。在通信网络中,SPN网络具备小世界复杂网络特性,针对该复杂网络特性提出了一种基于K-shell及动力学模型的SPN关键节点识别算法。本文针对通信运营商SPN网络拓扑特性及动力学特征,通过构建复杂网络模型,抽取网络拓扑及动力学关键特征实现SPN网络关键节点识别。首先构建了SPN网络的拓扑图,基于最短路径算法构建网络故障传播模型。其次运用复杂网络分析方法,从网络拓扑及故障模型中提取能够表征节点重要性的特征([CB]、[CD]、[CC]、SoCF、FoP),并通过计算节点的故障信息与拓扑信息特征之间的Kendall相关系数,量化网络级联故障与拓扑结构之间的相关性。最后在相关性分析的基础上,使用HDBSCAN聚类算法对两类特征进行聚类分析。实验结果表明,在SPN网络关键节点识别中,可以采用动力学特征(SoCF和[CC])或(FoP和[CB])对网络关键节点进行有效识别。

tsk-shell:一种话题敏感的高影响力传播者发现算法

在社交网络中,挖掘高影响力的信息传播者,对微博服务中内容的流行度分析和预测是非常有价值的任务.与众多相关方法相比,k-shell分解(k-core)方法因其简洁高效、平均性能好的特点吸引了越来越多的研究人员的兴趣.但是,目前k-shell方法着重考虑节点在网络中的位置因素,而忽略了话题在信息传播中的影响.因此,为了利用用户历史数据中蕴含的话题对消息的传播概率进行细粒度的建模,提出了一种话题敏感的k-shell(topic-sensitive k-shell,tsk-shell)分解算法.在真实Twitter数据集上实验表明,在发现top k高影响力传播者任务中,tsk-shell比k-shell的性能平均提高了约40%,证明了tsk-shell算法的有效性.

基于介中心性及K-shell的脑网络核心节点评价方法

在对基于核磁共振成像技术重构得到的人脑结构网络的研究中,核心节点的识别是对全脑网络特性展开研究的基础,具有重要意义。给出了一种基于K-shell和介中心性的核心节点评价方法,首先使用以节点局部重要性为标准的度中心性、邻近中心性和介中心性三个中心性评价方法分别对人脑结构网络中的节点重要性展开评估和分析;接着利用以节点全局地位为标准的K-shell分解法对人脑结构网络的核心节点展开分析。实验结果显示,由于同时兼顾了脑网络节点的整体特性和局部特性,该方法能够更全面和准确地识别核心脑区节点。

Theoretical analysis of minimum metal foil thickness achievable by asymmetric rolling with fixed identical roll diameters

A novel approach is proposed for computing the minimum thickness of a metal foil that can be achieved by asymmetric rolling using rolls with identical diameter. This approach is based on simultaneously solving Tselikov equation for the rolling pressure and the modified Hitchcock equation for the roller flattening. To minimize the effect of the elastic deformation on the equal flow per second during the ultrathin foil rolling process, the law of conservation of mass was employed to compute the proportions of the forward slip, backward slip, and the cross shear zones in the contact arc, and then a formula was derived for computing the minimum thickness for asymmetric rolling. Experiment was conducted to find the foil minimum thickness for 304 steel by asymmetric rolling under the asymmetry ratios of 1.05, 1.15 and 1.30. The experimental results are in good agreement with the calculated ones. It was validated that the proposed formula can be used to calculate the foil minimum thickness under the asymmetric rolling condition.

一种基于K-shell影响力最大化的路径择优计算迁移算法

在移动边缘计算网络中,高效的计算迁移算法是移动边缘计算的重要问题之一.为了提高计算迁移算法性能,应用同类问题的相互转换性和最大化影响力模型,利用K-shell算法对边缘服务器进行等级划分,考虑边缘服务器负载过重问题,构建路径重叠(path overlap,PO)算法,引入通信质量、交互强度、列队处理能力等指标进行边缘服务器路径优化,将优化计算任务迁移路径问题转化为社会网络影响力最大化问题求解.基于K-shell影响力最大化思想,联合优化改进贪心与启发式算法,提出一种K-shell影响力最大化计算迁移(K-shell influence maximization computation offloading,Ks-IMCO)算法,求解计算迁移问题.与随机分配(random allocation,RA)算法、支持路径切换选择的(path selection with handovers,PSwH)算法在不同实验场景下对比分析,Ks-IMCO算法的能耗、延迟等明显提升,能有效提高边缘计算网络计算迁移的效率.

在线社会网络的k-shell结构研究

分析研究了Twitter与You Tube两个在线社会网络的结构。用k-shell(k-壳)分解法对网络分解,并对比分析了它们的入(出)度、入(出)k-shell、以及度与k-shell之间的关系,发现它们之间有较大的差异。You Tube的入(出)度、入(出)k-shell分布均服从幂律分布,而Twitter的分布服从漂移幂律分布、指数截断的幂律分布,但它们的度与k-shell关系基本相同,都未表现出较强的相关性。此外,根据度相关系数的定义还提出k-shell相关性的定义及其计算方法,并用来刻画网络k-shell之间的同(异)配性。