The Bivariate Transmuted Family of Distributions: Theory and Applications

The bivariate distributions are useful in simultaneous modeling of two random variables. These distributions provide a way to model models. The bivariate families of distributions are not much widely explored and in this article a new family of bivariate distributions is proposed. The new family will extend the univariate transmuted family of distributions and will be helpful in modeling complex joint phenomenon. Statistical properties of the new family of distributions are explored which include marginal and conditional distributions, conditional moments, product and ratio moments, bivariate reliability and bivariate hazard rate functions. The maximum likelihood estimation (MLE) for parameters of the family is also carried out. The proposed bivariate family of distributions is studied for the Weibull baseline distributions giving rise to bivariate transmuted Weibull (BTW) distribution. The new bivariate transmuted Weibull distribution is explored in detail. Statistical properties of the new BTW distribution are studied which include the marginal and conditional distributions, product, ratio and conditional momenst. The hazard rate function of the BTW distribution is obtained. Parameter estimation of the BTW distribution is also done. Finally, real data application of the BTW distribution is given. It is observed that the proposed BTW distribution is a suitable fit for the data used.     

Thermal conductivity of liquid n-alkanes

The thermal conductivity of liquids has been shown in the past to be difficult to predict with a reasonable accuracy, due to the lack of accurate experimental data and reliable prediction schemes. However, data of a high accuracy, and covering wide density ranges, obtained recently in laboratories in Boulder, Lisbon, and London with the transient hot-wire technique, can be used to revise an existing correlation scheme and to develop a new universal predictive technique for the thermal conductivity of liquid normal alkanes. The proposed correlation scheme is constructed on a theoretically based treatment of the van der Waals model of a liquid, which permits the prediction of the density dependence and the thermal conductivity of liquid n-alkanes, methane to tridecane, for temperatures between 110 and 370 K and pressures up to 0.6 MPa, i.e., for 0.3T/T _c0.7 and 2.4P/P _c3.7, with an accuracy of ±1%, given a known value of the thermal conductivity of the fluid at the desired temperature. A generalization of the hard-core volumes obtained, as a function of the number of carbon atoms, showed that it was possible to predict the thermal conductivity of pentane to tetradecane±2%, without the necessity of available experimental measurements.     

Randomized range-maxima in nearly-constant parallel time

Given an array ofn input numbers, therange-maxima problem is that of preprocessing the data so that queries of the type what is the maximum value in subarray [i..j] can be answered quickly using one processor. We present a randomized preprocessing algorithm that runs inO(log^* n) time with high probability, using an optimal number of processors on a CRCW PRAM; each query can be processed in constant time by one processor. We also present a randomized algorithm for a parallel comparison model. Using an optimal number of processors, the preprocessing algorithm runs inO( (n)) time with high probability; each query can be processed inO ( (n)) time by one processor. (As is standard, (n) is the inverse of Ackermann function.) A constant time query can be achieved by some slowdown in the performance of the preprocessing stage.     

一种新的红外图像快速分割方法研究

研究红外图像目标分割快速优化问题。在高分辨率红外图像的分割中,红外图像存在数据量大、目标的边缘模糊和噪声较大等导致分辨率低和实时性差。为了快速准确分割,提出基于低尺度分割阈值预测的快速红外图像分割方法(LFIRS)。首先建立尺度阶数计算模型以确定保留原始红外图像目标基本信息所需的最小尺度,在分析多尺度过程对具有目标/背景强相关特性的红外图像进行分割阈值,建立多尺度红外图像分割阈值的相关模型(CLM),结合经典二维阈值法得到的最低两个尺度的阈值CLM模型参数,可以通过CLM模型与最小尺度的快速获取原始尺度的分割阈值,实现红外图像的快速分割。实验结果表明,改进方法提高了图像分辨和分割速度,且改善了分割效果。     

人群头发元素分布及某些特征研究

本文介绍用堆中子活化分析法测定人群头发中I、Br、Mg、Mn、Cu、Na、V、Cl、Al、Ca、S等11种元素。研究人发中元素分布特征、相关性特征、性别年令分布特征。方法学中还从法庭科学应用角度介绍同一性识别中差异率和重合几率的双判据方法。     

大气电场倒转与突发钠层及突发E层的相关性

突发钠层(Sporadic Sodium Layer, Na_S)是中高层大气金属层最为显著的一种现象,其发生机制目前尚无定论。突发E层(Sporadic E layer, E_S)是等离子体密度异常增大的薄层,被认为与Na_S密切相关。为进一步研究Na_S及E_S事件之间相关性及影响因素,利用中国科学院“子午工程”2010～2018年合肥科大站宽带钠荧光共振激光雷达观测结果,并结合武汉左岭镇站数字测高仪及九峰站大气电场仪数据,分析大气电场倒转(即北向电场)对Na_S以及E_S事件的影响。在统计的91例Na_S事件中,发生于大气电场倒转时的比例为20/91; 同时,在发生Na_S事件的事例中,E_S消失或中断的比例较大(14/20),表明E_S可能以提供钠源的形式转化为Na_S。此外,在分析武汉左岭镇站数字测高仪数据的同时进行概率统计,结果表明:当大气电场倒转时,E_S临界频率减小甚至消失的概率较大(187/242),少数情况下可能造成临界频率增大甚至激发E_S生成(55/242); E_S虚高消失比例为179/242,E_S不变比例为27/242,E_S上升比例为23/242。综上所述,大气北向电场在一定程度上对E_S事件的发生有抑制作用,并对E_S事件的发生高度有明显影响。最后,对一种与电场倒转相关的突发钠层机制也进行了讨论。     

敏捷化AIOps框架及运维数据质量评估方法

敏捷化智能运维(AIOps)框架将模型构建提前至测试阶段,利用该阶段产生的监控数据代替线上采集的数据以训练AIOps模型,进而实现智能运维的早开发与早使用. 运维数据质量评估方法通过最大均值差异度量方式,分别在健康评估与故障诊断运维场景下对训练数据分别进行趋势性、阶段性、可检测性及可诊断性评估,以预估数据对模型的适用性. 基于华为技术有限公司提供的测试环境设置测试用例并构建实验数据集,在该数据集上的实验结果验证了敏捷化AIOps框架的可行性及数据质量评估方法的有效性.     

一种新颖的低层视觉特征到高层语义的映射方法*

通过在低层视觉特征上提取图像的局部颜色和纹理特征,再利用模糊神经网络建立低层视觉特征和高层语义特征之间的映射,实现了图像属性信息的有效传递和可靠检索.最后,为了提高检索效率,把相关反馈引进到图像检索系统中.实验证明,该方法取得了较好的检索查全率和准确率.     

基于CCA的人耳和侧面人脸特征融合的身份识别*

鉴于人耳和人脸特殊的生理位置关系,从非打扰识别的角度出发,提出仅采集侧面人脸图像,利用典型相关分析的思想提取人耳和侧面人脸的关联特征,进行人耳和侧面人脸在特征层的融合.实验结果表明,此方法与单一的人耳或侧面人脸特征识别比较,识别率得到提高.     

相对压强对白炭黑氮吸附表面积测试稳定性的影响

研究相对压强对白炭黑氮吸附表面积测试稳定性的影响。结果表明:在相同液氮纯度、脱气温度、脱气时间、氮吸附点数量条件下,与相对压强范围为0.05~0.1时相比,相对压强范围为0.05~0.2时白炭黑的氮吸附表面积测量值偏低,且差值随氮吸附表面积的增大呈增大趋势;相对压强范围较小时,氮吸附表面积测试结果的线性相关因数较大,再现性较好,测试结果较稳定。