Distributed Weighted Data Aggregation Algorithm in End-to-Edge Communication Networks Based on Multi-armed Bandit

As a combination of edge computing and artificial intelligence,edge intelligence has become a promising technique and provided its users with a series of fast,precise,and customized services.In edge intelligence,when learning agents are deployed on the edge side,the data aggregation from the end side to the designated edge devices is an important research topic.Considering the various importance of end devices,this paper studies the weighted data aggregation problem in a single hop end-to-edge communication network.Firstly,to make sure all the end devices with various weights are fairly treated in data aggregation,a distributed end-to-edge cooperative scheme is proposed.Then,to handle the massive contention on the wireless channel caused by end devices,a multi-armed bandit(MAB)algorithm is designed to help the end devices find their most appropriate update rates.Diffe-rent from the traditional data aggregation works,combining the MAB enables our algorithm a higher efficiency in data aggregation.With a theoretical analysis,we show that the efficiency of our algorithm is asymptotically optimal.Comparative experiments with previous works are also conducted to show the strength of our algorithm.

Multivariate Aggregated NOMA for Resource Aware Wireless Network Communication Security

NonorthogonalMultiple Access(NOMA)is incorporated into the wireless network systems to achieve better connectivity,spectral and energy effectiveness,higher data transfer rate,and also obtain the high quality of services(QoS).In order to improve throughput and minimum latency,aMultivariate Renkonen Regressive Weighted Preference Bootstrap Aggregation based Nonorthogonal Multiple Access(MRRWPBA-NOMA)technique is introduced for network communication.In the downlink transmission,each mobile device’s resources and their characteristics like energy,bandwidth,and trust are measured.Followed by,the Weighted Preference Bootstrap Aggregation is applied to recognize the resource-efficient mobile devices for aware data transmission by constructing the different weak hypotheses i.e.,Multivariate Renkonen Regression functions.Based on the classification,resource and trust-aware devices are selected for transmission.Simulation of the proposed MRRWPBA-NOMA technique and existing methods are carried out with different metrics such as data delivery ratio,throughput,latency,packet loss rate,and energy efficiency,signaling overhead.The simulation results assessment indicates that the proposed MRRWPBA-NOMA outperforms well than the conventional methods.

Experimental Investigation and Development of Artificial Neural Network Model for the Properties of Locally Produced Light Weight Aggregate Concrete

The developments in the field of construction raise the need for concrete with less weight. This is beneficial for different applications starting from the less load applied to foundations and soil till the reduction of carnage capacity required for lifting precast units. In this paper, the production of light weight concrete from light local weight aggregate is investigated. Three candidate materials are used: crushed fired brick, vermiculite and light exfoliated clay aggregate (LECA). The first is available as the by-product of brick industry and the later two types are produced locally for different applications. Nine concrete mixes were made with same proportions and different aggregate materials. Physical and mechanical properties were measured for concrete in fresh and hardened states. Among these measured ones are unit weight, slump, compressive and tensile strength, and impact resistance. Also, the performance under elevated temperature was measured. Results show that reduction of unit weight up to 45%, of traditional concrete, can be achieved with 50% reduction in compressive strength. This makes it possible to get structural light weight concrete with compressive strength of 130 kg/cm2. Light weight concrete proved also to be more impact and fire resistant. However, as expected, it needs separate calibration curves for non-destructive evaluation. Following this experimental effort, the Artificial Neural Network (ANN) technique was applied for simulating and predicting the physical and mechanical properties of light weight aggregate concrete in fresh and hardened states. The current paper introduced the (ANN) technique to investigate the effect of light local weight aggregate on the performance of the produced light weight concrete. The results of this study showed that the ANN method with less effort was very efficiently capable of simulating the effect of different aggregate materials on the performance of light weight concrete.

Time Dependent Surface Heat Transfer in Light Weight Aggregate Cement Based Materials

Surface temperature changes of building materials affect the calculation of heat flow and thus the energy use in heating and cooling. The surface heat transfer coefficient , limiting the heat flow between material surface and ambient air is normally taken as a constant. In this study we propose a time-dependent function . We estimate from unidirectional heat flow experiments with transient and steady-state conditions. Using temperature measurements and the conservation of energy at the surface including convective and irradiative boundary conditions, the value of was obtained both using Finite Difference and Taylor Polynomials methods. Numerical solutions of temperature distribution as function of time were improved with the obtained -functions compared to with constant . There were no clear difference between on different materials, and the final values observed were in the order of magnitude expected from the literature.

Effects of Spherical Light-weight Aggregates Additions on Workability and Mechanical Properties of Al_2O_3-SiO_2 System Castables

In order to clarify the effect of spherical light-weight aggregates addition on properties of A12 07 - Si02 system castables, adopting ATO mullite traditional light-weight aggregates and ATO mullite spherical light-weight aggre- gates, bauxite homogenization powder, microsilica , cal- cium aluminate cement as main raw materials, light- weight Al2 03 - SiO2 system castables were prepared by replacing conventional light-weight aggregate with spherical light-weight aggregates. The effects of spheri- cal light-weight aggregates addition on workability, me- chanical properties of castables after heated at different temperatures were researched; the microstructure of the aggregates was analyzed by SEM. The result shows that the introduction of spherical light-weight aggregates can significantly improve the flowability and reduce the water addition of the castables. Water demand of the castable is reduced from 18% with the conventional light-weight aggregates to 14% with spherical light-weight aggre- gates. In addition, light-weight castables prepared by spherical aggregates can keep the same workability with- in a wider range of water addition. Therefore, spherical aggregates are user-friendly. The introduction of spheri- cal light-weight aggregates is favorable to packing densi- ty and mechanical properties of castables, such as cold crushing strength, cold modulus of rupture, hot modulus of rupture at 1 200℃.

How freezing and thawing processes affect black-soil aggregate stability in northeastern China

Laboratory experiments were carried out to investigate the effect of freezing and thawing processes on wet aggregate stability （WAS） of black soil. Wet aggregate stability was determined by different aggregate size groups, different water contents, various freeze-thaw cycles, and various freezing temperatures. The results showed that, when at suitable water content, aggregate stability was enhanced, aggregate sta-bility will be disrupted when moisture content is too high or too low, especially higher water content. Temperature also had a significant ef-fect, but moisture content determined the suitable freezing temperatures for a given soil. Water-stable aggregate （WSA〉0.5）, the total aggre-gate content, and mean weight diameter decreasing with the freeze-thaw cycles increase, reached to 5 percent significance level. The reason for crumbing aggregates is the water and air conflict, thus raising the hypothesis that water content affects the aggregate stability in the process of freezing and thawing.

Molecular Weight and Aggregation of Erwinia Gum in Aqueous Solutions

Erwinia(E) gum is composed of glucose, fucose, galactose and glucuronic acid. The weightaverage molecular weights M w, numberaverage molecular weights M n and intrinsic viscosities[η] of the four fractions and the unfractionated E gum in aqueous solutions at desired temperatures were studied by light scattering, membrane osmometry, size exclusion chromatography(SEC) and viscometry. The experimental results prove that E gum formed aggregates in the aqueous solution at 25 ℃ and the aggregates were broken gradually with increasing temperature. The dissociation of the aggregates of E gum in the aqueous solution started at 36 ℃, and was completed at around 90 ℃. The [η] values of E gum and its fractions are much higher than those of the conventional polymers with the similar molecular weights, and decrease with increasing NaCl concentration.

基于自适应窗的动态权值代价聚合立体匹配

传统局部匹配算法通常在不同聚合窗口下采用单一权值进行代价聚集,而忽略了不同区域像素点之间的差异性,易导致基于双目视觉测量的立体匹配精度不稳定。为此,提出一种基于自适应窗的动态权值代价聚合立体匹配算法。首先,以梯度信息表征模型为约束条件,构建代价聚合自适应十字交叉窗口。其次,分析视差不连续区域与弱纹理区域的像素特征,建立基于像素距离与色差双阈值权重的代价聚集模型,进而计算各窗口的动态权重影响因子。最后,基于线性迭代聚类法分割视差图区域,剔除奇异的视差值以提高算法匹配精度。实验结果表明,在Middlebury数据集的测试中,所提算法的平均非遮挡区域和全部区域的误匹配率分别为4.11%和5.65%,优于传统匹配算法;4组测量样品的全局长度测量平均相对误差小于1.2%,全局高度测量平均相对误差小于2.7%。实验结果检验了所提算法的有效性和可靠性。

基于聚落的人口统计数据空间分解算法

利用人口密度随机森林模型探讨人口密度与影响因子之间的非线性关系,是当前人口分布研究的前沿,但人口统计数据在空间分解过程中非正规约束下的最优输运问题尚未妥善解决。本文基于面积加权法,以矢量格式的村人口数据集为起点,以矢量格式的聚落和公顷网格数据集为约束,设计了一套顾及聚落分布的人口统计数据空间分解算法。通过将村常住人口数据依次分解至聚落和公顷网格之中,获得了栅格人口密度数据集(SJZ_RK)。分析表明,SJZ_RK数据集的人口总数为1039.60万人,仅产生0.04%的误差,说明本文提出的人口统计数据空间分解算法具有较高准确度。经测算,SJZ_RK数据集的人口分布基尼系数(0.8909)>GHS_POP(0.8548)>SJZ_CUN_RK(0.5898)>GPWv4(0.5897),说明考虑聚落分布状况的SJZ_RK数据集很好地刻画了人口分布的空间集聚和异质性特征,为构建人口密度随机森林模型等监督类机器学习模型训练样本提供了高质量的人口密度标签数据。在刻画非聚落区、城市聚落区、值域范围方面,SJZ_RK数据集更接近实际情况,其在前两方面优于GHS_POP数据集,其在这3个方面均显著优于SJZ_CUN_RK和GPWv4两个数据集。本文算法破解了2个难题:①优化了获取高精度栅格人口密度数据集的计算程序,实现了相对准确的人口分布离散化表达;②统一了人口密度标签数据和影响因子数据的粒度,从而为人口密度随机森林模型训练样本摆脱MAUP的困扰,为克服人口密度随机森林模型的区群谬误问题,创造了必要条件。

对位芳纶的结构与缺陷对其力学性能的影响

聚对苯二甲酰对苯二胺(PPTA)纤维具有优异的力学性能、耐化学腐蚀性能以及阻燃性能,在航空航天、国防、民用等领域得到了广泛应用,是一种新型战略性材料。对4种不同规格的对位芳纶的力学性能、相对分子质量、聚集态结构以及纤维表面及内部缺陷进行研究,建立纤维结构、缺陷与性能之间的关系。结果表明:在具有相同化学分子结构的前提下,聚合物相对分子质量是影响纤维力学性能的重要因素之一,随着相对分子质量的增加,纤维的强度和模量增加。对位芳纶的拉伸强度主要与其结晶度、取向度、表面缺陷以及内部微孔缺陷有关,其中结晶度和微孔缺陷最为重要。纤维的模量主要与纤维的取向度有关,结晶度及纤维内外部缺陷对纤维模量的影响较小。

高效联邦学习:范数加权聚合算法

在联邦学习中,跨客户端的非独立同分布(non-IID)数据导致全局模型收敛较慢,通信成本显著增加。现有方法通过收集客户端的标签分布信息来确定本地模型的聚合权重,以加快收敛速度,但这可能会泄露客户端的隐私。为了在不泄露客户端隐私的前提下解决non-IID数据导致的收敛速度降低的问题,提出FedNA聚合算法。该算法通过两种方法来实现这一目标。第一,FedNA根据本地模型类权重更新的L 1范数来分配聚合权重,以保留本地模型的贡献。第二,FedNA将客户端的缺失类对应的类权重更新置为0,以缓解缺失类对聚合的影响。在两个数据集上模拟了四种不同的数据分布进行实验。结果表明,与FedAvg相比,FedNA算法达到稳定状态所需的迭代次数最多可减少890次,降低44.5%的通信开销。FedNA在保护客户端隐私的同时加速了全局模型的收敛速度,降低了通信成本,可用于需要保护用户隐私且对通信效率敏感的场景。

面向对象高分影像归纳式图神经网络分类法

传统面向对象分类多采用遥感影像的光谱特征,忽略了影像对象之间的空间特征。本文提出了一种采用改进归纳式图神经网络的高分遥感影像面向对象分类方法,实现了光谱-空间复合节点相似度的融合系数自适应调节,以及邻域节点采样最佳数量的自动确定。首先,改进KNN图构建方法,采用标准差信息量评价法确定用于构建光谱特征和空间特征的复合节点相似度的融合系数;然后,利用反馈曲线法确定最佳的采样邻域节点数量,使用GraphSAGE节点嵌入完成特征表达;最后,依托Softmax函数预测节点类别。以GID和BDCI2017数据集为试验数据,本文的构图方法相较于改进前的构图方法在分类精度上有所提升。本文分类方法的平均Kappa系数和总体精度分别优于CART分类树算法、GCN算法、GAT算法、LANet算法、CCTNet算法和SLCNet算法0.31、0.14、0.13、0.12、0.08、0.02和42.31%、7.4%、6.73%、8.69%、6.03%、1.52%,并且在植被和建设用地提取上具有较好的稳健性。本文方法为高分遥感影像土地覆盖分类提供了有效的工具。

作战效能典型评估方法特性分析

针对现阶段作战效能评估方法种类繁多,原理、适用范围不同,导致装备作战效能评估方法选取困难,以作战效能评估典型流程为切入点,重点对作战效能典型评估方法特性进行分析研究。首先,系统梳理了常用的数据预处理和赋权方法,从数学机理上入手,进行特性和适用范围分析;然后,从指标关系入手,介绍了聚合方法的处理步骤,并简要论述了典型作战效能评估模型的特性和适用范围;最后,利用实例计算研究评估模型与关键方法之间的关系,即数据预处理和赋权方法对能力聚合结果的影响。通过研究指出,需要掌握装备作战效能典型评估方法特性,根据具体指标数据结构选取合适的方法,才能客观准确地评估装备作战效能。专家打分法综合考虑作战实际,原理简单,操作方便,在作战效能评估过程中优势明显,可优先考虑专家打分赋权法。

MCDM technique using single-valued neutrosophic trigonometric weighted aggregation operators

Motivated based on the trigonometric t-norm and t-conorm,the aims of this article are to present the trigonometric t-norm and t-conorm operational laws of SvNNs and then to propose the SvNN trigonometric weighted average and geometric aggregation operators for the modelling of a multiple criteria decision making(MCDM)technique in an inconsistent and indeterminate circumstance.To realize the aims,this paper first proposes the trigonometric t-norm and t-conorm operational laws of SvNNs,which contain the hybrid operations of the tangent and arctangent functions and the cotangent and inverse cotangent functions,and presents the SvNN trigonometric weighted average and geometric operators and their properties.Next,an MCDM technique is proposed in view of the presented two aggregation operators in the circumstance of SvNNs.In the end,an actual case of the choice issue of slope treatment schemes is provided to indicate the practicability and effectivity of the proposed MCDM technique.

基于改进麻雀算法的配电网故障定位

针对配电网故障定位准确率低、容错率低的问题,提出了一种基于改进麻雀搜索算法的配电网故障区段定位方法.在麻雀算法中引入动态自适应权重,加快麻雀算法的收敛速度,增强其局部开发和全局搜索的能力.通过在种群初始迭代中增加聚集阈值,提高算法的寻优精度.通过对单一故障场景、多故障场景下进行仿真测试验证改进麻雀算法的准确性和容错性,在IEEE33节点场景下,将改进后的麻雀搜索算法与粒子群算法、蛇算法、麻雀算法进行了比较,验证了改进后的麻雀算法的优越性,能够准确快速地实现故障定位.结果表明,改进后的麻雀搜索算法寻优能力更强,容错性更高.

Aggregating metasearch engine results based on maximal entropy OWA operator

The maximal entropy ordered weighted averaging （ME-OWA） operator is used to aggregate metasearch engine results, and its newly analytical solution is also applied. Within the current context of the OWA operator, the methods for aggregating metasearch engine results are divided into two kinds. One has a unique solution, and the other has multiple solutions. The proposed method not only has crisp weights, but also provides multiple aggregation results for decision makers to choose from. In order to prove the application of the ME-OWA operator method, under the context of aggregating metasearch engine results, an example is given, which shows the results obtained by the ME-OWA operator method and the minimax linear programming （ minimax-LP ） method. Comparison between these two methods are also made. The results show that the ME-OWA operator has nearly the same aggregation results as those of the minimax-LP method.

低分子肝素钠联合硝苯地平治疗妊娠期高血压患者的效果

目的:观察低分子肝素钠联合硝苯地平治疗妊娠期高血压患者的效果。方法:选取2020年1月至2023年1月该院收治的168例妊娠期高血压患者进行前瞻性研究,按照随机数字表法将其分为对照组和研究组各84例。对照组采用硝苯地平治疗,研究组在对照组基础上联合低分子肝素钠治疗,比较两组妊娠结局、临床疗效、治疗前后血压(收缩压、舒张压)水平、血管内皮功能指标[内皮素-1(ET-1)、同型半胱氨酸(Hcy)]和氧化应激指标[丙二醛(MDA)、超氧化物歧化酶(SOD)]水平、血小板聚集率和黏附率、不良反应发生率。结果:研究组阴道分娩率高于对照组,剖宫产率低于对照组,差异有统计学意义(P<0.05);研究组治疗总有效率为94.05%(79/84),高于对照组的80.95%(68/84),差异有统计学意义(P<0.05);治疗后,两组收缩压、舒张压水平均低于治疗前,且研究组低于对照组,差异有统计学意义(P<0.05);治疗后,两组ET-1、Hcy、MDA水平均低于治疗前,且研究组低于对照组,两组SOD水平均高于治疗前,且研究组高于对照组,差异有统计学意义(P<0.05);两组血小板聚集率、黏附率均低于治疗前,且研究组低于对照组,差异有统计学意义(P<0.05);两组治疗期间均未发生明显不良反应。结论:低分子肝素钠联合硝苯地平治疗妊娠期高血压患者,可改善妊娠结局,提高临床疗效,降低血压,抑制血小板聚集,缓解氧化应激反应,效果优于单纯硝苯地平治疗。

Some OWA operator weights determination methods with RIM quantifier

Based on the quantifier guided method,an ordered weighted averaging(OWA)weights generating method under given orness level with regular increasing monotone(RIM)quantifiers is proposed.Then the RIM quantifier based OWA weights generating method is modified to make the generated weights be monotonic,which can be used to express the decision maker's consistent preference information.Finally,both of these weights generating methods are extended to their generic forms,so that they can generate the OWA weights for any ordinary elements set with any given aggregated value.

秦岭中段北麓农耕地秸秆还田对土壤团聚体及可蚀性季节性变化的影响

选取秦岭中段北麓陕西关中地区典型农业土壤塿土,添加小麦、大豆、玉米秸秆,并选择无秸秆添加作为对照。秸秆混入375 d,共采集样品11次,探究秸秆混入对团聚体特征及可蚀性季节性变化的影响。结果表明:(1)土壤有机质呈现明显的季节性变化,随着秸秆混入时间的延长,土壤有机质含量呈上升趋势;与混入前相比,实验结束时添加小麦、大豆、玉米秸秆的处理有机质含量分别提高了19.56%、18.28%、18.61%。(2)秸秆混入降低了小于1 mm团聚体比例,增加了大于1 mm团聚体占比;与混入前相比,实验结束时添加小麦、大豆和玉米秸秆三种处理的平均重量直径(MWD)分别提高了67.31%、68.53%、56.98%,几何平均直径(GMD)分别提高了45.77%、35.00%、40.25%。(3)与裸地相比,混入秸秆样地的土壤可蚀性值均显著降低,添加小麦、大豆、玉米秸秆处理的土壤可蚀性平均值分别降低了28.92%、23.33%、26.40%。研究结果探明了秸秆混入对土壤团聚体特征和土壤可蚀性的季节性变化的影响,对我国南北过渡带水土流失区农业生产实践具有重要的参考价值。

强震区高墩大跨连续刚构桥轻量化设计与减震研究

为保证强震区高墩大跨连续刚构桥抗震充分安全,提出了使用轻质材料及波纹钢腹板减重的轻量化设计和在双肢薄壁墩间设置阻尼耗能装置的两种方案。采用Midas Civil建立某双肢薄壁墩大跨连续刚构桥有限元模型,选取3条人工地震波及3条常用地震波对其进行动力时程分析。同时综合对比了双肢薄壁墩顺桥向设置RC系梁、防屈曲支撑(BRB)和转动铅耗能阻尼器对其减震性能的影响。结果表明:采用波纹钢腹板箱梁和轻骨料混凝土进行轻量化设计能明显提升桥梁的抗震性能,墩顶及墩底弯矩最大降低约20%,减重设计可作为提高桥梁抗震性能的有效途径。相比于传统RC系梁,设置BRB(斜撑)和转动铅耗能阻尼器能显著降低地震作用下桥墩的受力,墩顶位移和墩底弯矩最大分别降低约15%和30%,且BRB和转动铅耗能阻尼器耗能良好。轻量化设计和减震控制可作为高墩大跨连续刚构抗震性能提升的有效措施。