Interpolation Method of Head-Related Transfer Functions Based on Common-Pole/Zero Modeling

The head-related transfer function(HRTF)involves the cues for human auditory localization,which turns it into an essential item of virtual auditory display technology.In practice,the interpolation of HRTF is necessary for the virtual auditory display systems to achieve high spatial resolution.Traditional geometric-based interpolation methods are generally restrained by the spatial distribution of reference on HRTF.When the spatial distribution is sparse,the accuracy of interpolation decreases significantly.Therefore,an interpolation method using the common-pole/zero model and the fitting neural network is proposed.First,we propose a common-pole/zero model to represent HRTFs across multiple subjects,in which the low-dimensional features of the measured HRTFs are extracted.Then,for a new spatial direction,we predict the corresponding low-dimensional HRTF with a fitting neural network.Finally,we reconstruct the high-dimensional HRTF from the predicted low-dimensional HRTF.The simulation results suggest that the proposed method outperforms other interpolation methods such as Linear_AMBC,Bilinear_AMBC,and the Combination method.

基于MIKE ZERO 2020的郁江贵港河段一维水质模型

基于MIKE ZERO 2020软件中的HD水动力学模块和AD对流扩散模块,建立郁江贵港市河段的水文、水质信息耦合模型,对郁江贵港河段的水位、流量以及污染物在水体中迁移扩散衰减情况进行了模拟分析。根据郁江近年来的水文资料对模型进行率定并验证。将该模型应用于2023年6月21日~7月6日的洪水过程,结果表明,所建立的模型在率定和验证及应用期间模拟效果均表现良好,模拟精度高。充分证明该模型适用于模拟郁江贵港河段的水文、水质信息变化特征,为提高贵港市防洪、水情预报及水污染预测提供了重要的技术支撑。

Modelling tree mortality across diameter classes using mixedeffects zero-inflated models

The mortality of trees across diameter class model is a useful tool for predicting changes in stand structure.Mortality data commonly contain a large fraction of zeros and general discrete models thus show more errors.Based on the traditional Poisson model and the negative binomial model,different forms of zero-inflated and hurdle models were applied to spruce-fir mixed forests data to simulate the number of dead trees.By comparing the residuals and Vuong test statistics,the zero-inflated negative binomial model performed best.A random effect was added to improve the model accuracy;however,the mixed-effects zero-inflated model did not show increased advantages.According to the model principle,the zeroinflated negative binomial model was the most suitable,indicating that the"0"events in this study,mainly from the sample"0",i.e.,the zero mortality data,are largely due to the limitations of the experimental design and sample selection.These results also show that the number of dead trees in the diameter class is positively correlated with the number of trees in that class and the mean stand diameter,and inversely related to class size,and slope and aspect of the site.

Bayesian zero-failure reliability modeling and assessment method for multiple numerical control(NC) machine tools

A new problem that classical statistical methods are incapable of solving is reliability modeling and assessment when multiple numerical control machine tools(NCMTs) reveal zero failures after a reliability test. Thus, the zero-failure data form and corresponding Bayesian model are developed to solve the zero-failure problem of NCMTs, for which no previous suitable statistical model has been developed. An expert-judgment process that incorporates prior information is presented to solve the difficulty in obtaining reliable prior distributions of Weibull parameters. The equations for the posterior distribution of the parameter vector and the Markov chain Monte Carlo(MCMC) algorithm are derived to solve the difficulty of calculating high-dimensional integration and to obtain parameter estimators. The proposed method is applied to a real case; a corresponding programming code and trick are developed to implement an MCMC simulation in Win BUGS, and a mean time between failures(MTBF) of 1057.9 h is obtained. Given its ability to combine expert judgment, prior information, and data, the proposed reliability modeling and assessment method under the zero failure of NCMTs is validated.

Comparative Assessment of Zero-Inflated Models with Application to HIV Exposed Infants Data

In a typical Kenyan HIV clinical setting, there is a likelihood of registering many zeros during the routine monthly data collection of new HIV infections among HIV exposed infants (HEI). This is attributed to the implementation of the prevention of mother to child transmission (PMTCT) policies. However, even though the PMTCT policy is implemented uniformly across all public health facilities, implementation naturally differs from every facility due to differential health systems and infrastructure. This leads to structured zero among reported positive HEI (where PMTCT implementation is optimum) and non-structured zero among reported positive HEI (where PMTCT implementation is not optimum). Hence the classical zero-inflated and hurdle models that do not account for the abundance of structured and non-structured zeros in the data can give misleading results. The purpose of this study is to systematically compare performance of the various zero-inflated models with an application to HIV Exposed Infants (HEI) in the context of structured and unstructured zeros. We revisit zero-inflated, hurdle models, Poisson and negative binomial count models and conduct the simulations by varying sample size and levels of abundance zeros. Results from simulation study and real data analysis of exposed infant diagnosis show the negative binomial emerging as the best performing model when fitting data with both structured and non-structured zeros under various settings.

Numerical modeling of zero-offset laboratory data in a strong topographic environment: results for a spectral-element method and a discretized Kirchhoff integral method

Abstract Accurate simulation of seismic wave propaga- tion in complex geological structures is of particular interest nowadays. However conventional methods may fail to simulate realistic wavefields in environments with great and rapid structural changes, due for instance to the presence of shadow zones, diffractions and/or edge effects. Different methods, developed to improve seismic model- ing, are typically tested on synthetic configurations against analytical solutions for simple canonical problems or ref- erence methods, or via direct comparison with real data acquired in situ. Such approaches have limitations,especially if the propagation occurs in a complex envi- ronment with strong-contrast reflectors and surface irreg- ularities, as it can be difficult to determine the method which gives the best approximation of the ＂real＂ solution, or to interpret the results obtained without an a priori knowledge of the geologic environment. An alternative approach for seismics consists in comparing the synthetic data with high-quality data collected in laboratory experi- ments under controlled conditions for a known configuration. In contrast with numerical experiments, laboratory data possess many of the characteristics of field data, as real waves propagate through models with no numerical approximations. We thus present a comparison of laboratory-scaled measurements of 3D zero-offset wave reflection of broadband pulses from a strong topographic environment immersed in a water tank with numerical data simulated by means of a spectral-element method and a discretized Kirchhoff integral method. The results indicate a good quantitative fit in terms of time arrivals and acceptable fit in amplitudes for all datasets.

A Note on the Characterization of Zero-Inflated Poisson Model

Zero-Inflated Poisson model has found a wide variety of applications in recent years in statistical analyses of count data, especially in count regression models. Zero-Inflated Poisson model is characterized in this paper through a linear differential equation satisfied by its probability generating function [1] [2].

Asymptotic Comparison of Method of Moments Estimators and Maximum Likelihood Estimators of Parameters in Zero-Inflated Poisson Model

This paper discusses the estimation of parameters in the zero-inflated Poisson (ZIP) model by the method of moments. The method of moments estimators (MMEs) are analytically compared with the maximum likelihood estimators (MLEs). The results of a modest simulation study are presented.

个体化频带滑动窗特征的轻度认知障碍诊断研究

轻度认知障碍(MCI)是老年性痴呆诊断的关键阶段,脑电(EEG)信号特征可以反映MCI患者的认知状态,帮助实现早期诊断。现有研究在EEG特征提取过程中,针对脑电各节律,大多采用固定的时间窗完成分段处理,忽略了不同节律的特征差异,从而影响诊断效果。针对该问题,本文提出了一种新的组合滑动窗优化算法,该算法通过迭代振幅调整傅里叶变换(IAAFT)对零模型的构建方法进行了改进,以此得到评估大脑动态特性指标KPLI,通过对EEG各频段信号采取多种滑动窗组合,并以KPLI指标引导,得到适合不同频段的最佳滑动窗组合。在最佳滑动窗组合基础上,对各频段组合提取相位滞后指数(PLI),进行连续小波变换(CWT)特征,通过ResNet-MLP双通道分类网络实现MCI诊断。结果显示,使用个性化组合频段滑动窗对88名受试者(32名MCI患者,36名阿尔茨海默症患者以及20名正常对照组)实现了诊断分类,得到了82.2%的分类准确率,比固定窗的分类提高了10%(得到了72.2%的分类准确率)。结果表明,基于个体化脑电节律特征组合能够更好提取MCI的特征,提高轻度认知障碍诊断的正确率与特异性,是一种有效的脑电特征提取方法。

Zero Truncated Bivariate Poisson Model: Marginal-Conditional Modeling Approach with an Application to Traffic Accident Data

A new covariate dependent zero-truncated bivariate Poisson model is proposed in this paper employing generalized linear model. A marginal-conditional approach is used to show the bivariate model. The proposed model with estimation procedure and tests for goodness-of-fit and under (or over) dispersion are shown and applied to road safety data. Two correlated outcome variables considered in this study are number of cars involved in an accident and number of casualties for given number of cars.

基于视觉-语言预训练模型的零样本迁移学习方法综述

近年来随着人工智能(AI)技术在计算机视觉与自然语言处理等单模态领域表现出愈发优异的性能,多模态学习的重要性和必要性逐渐展现出来,其中基于视觉-语言预训练模型的零样本迁移(ZST)方法得到了国内外研究者的广泛关注。得益于预训练模型强大的泛化性能,使用视觉-语言预训练模型不仅能提高零样本识别任务的准确率,而且能够解决部分传统方法无法解决的零样本下游任务问题。对基于视觉-语言预训练模型的ZST方法进行概述,首先介绍了零样本学习(FSL)的传统方法,并对其主要形式加以总结;然后阐述了基于视觉-语言预训练模型的ZST和FSL的区别及其可以解决的新任务;其次介绍了基于视觉-语言预训练模型的ZST方法在样本识别、目标检测、语义分割、跨模态生成等下游任务中的应用情况;最后对现有的基于视觉-语言预训练模型的ZST方法存在的问题进行分析并对未来的研究方向进行展望。

零信任的安全模型研究

零信任被认为是一种新的安全范式,从安全模型视角,揭示了零信任架构以“身份和数据”为主线的安全模型深化与整合.零信任以身份为核心建立全景管控实体链条,围绕实体属性功能生命周期等建立深度防御,并集中重定向实体间信息的流动,整合信息通道,实现层层防护和细粒度动态化访问控制,最后从攻击者视角在信息流通道关键节点设置主动防御机制.由于零信任系统一定会成为高价值资产,探讨了零信任系统演进中与业务深度融合、零信任自身安全和弹性服务能力的新趋势.通过对零信任蕴含安全模型和自身安全性的分析,期望能够为零信任在应用中的架构设计、技术演进、应用安全提供更加清晰的技术发展路径.

参照零模型的加权网络链路预测因素研究

基于零模型,文章研究了如何量化分析加权复杂网络中链路预测的影响因素。通过对1阶零模型、权重置乱零模型,结构置乱零模型在拓扑结构和权重相关性两个方面分别进行研究。以美国航空网络为实证网络,针对加权网络中的权重特性,分析不同权重连边的可预测性和对于链路预测的影响。结果表明,美国航空网中存在拓扑权重相关性,并且破环拓扑结构比破坏权重相关性对于链路预测的影响更大。

耦合均值-相关性的起重伤害事故致因ZIP模型研究

近些年来,起重伤害事故高发频发,导致了较大的直接经济损失和人员伤亡,受到行业的高度关注。为探究起重伤害事故致因的影响程度,采集2011—2021年376份起重伤害事故调查报告,依据事故致因24Model和系统安全分析法识别事故致因,构建起重伤害事故致因的零膨胀泊松回归模型(Zero-Inflated Poisson,ZIP),并通过Vuong方法和拟合优度检验准则进行检验;综合考虑事故致因发生频次的均值、致因和事故发生的相关性,运用弹性分析方法对事故致因的影响程度进行定量排序。结果表明:ZIP回归模型拟合效果优于泊松回归模型,各事故致因对起重伤害事故的影响程度排序为安全监管不到位C_(6)(T_(k)=1.0221)、安全意识淡薄H_(1)(T_(k)=0.5117)、作业人员违规作业H_(3)(T_(k)=0.4758)、作业人员无证上岗H_(2)(T_(k)=0.2116)、专项施工方案不合格C_(7)(T_(k)=0.1234)和结构构件破坏或连接不可靠M_(3)(T_(k)=0.1045)。研究从事故致因发生频次的均值、致因和事故发生的相关性两个维度刻画事故致因对起重伤害事故的影响程度,为起重伤害事故风险分级管控提供了新的研究思路和方法。

ZVT-PWM Buck变换器的小信号建模及数字控制

首先介绍了零电压转换-脉宽调制(ZVT-PWM)Buck变换器的工作原理。接着采用等效可控源平均法推导出了变换器的小信号模型以及传递函数的表达式。对小信号模型分析表明,ZVT-PWM Buck变换器比传统Buck变换器的瞬态响应特性更好。然后依据该小信号模型,设计了数字控制器的参数。最后对原理样机进行测试,实测的功率级传递函数验证了小信号模型的正确性,闭环下的负载瞬态响应测试过冲电压为410mV,恢复时间为150μs,优于传统Buck变换器的负载瞬态响应特性。

多元化干预联合零缺陷护理模式在颅脑损伤急诊手术患者中的应用效果

目的:分析多元化干预联合零缺陷护理模式在颅脑损伤急诊手术患者中的应用效果。方法:选取2022年1月—2023年6月于赣南医学院第一附属医院接受急诊颅脑损伤手术治疗的患者78例作为研究对象,随机分为对照组与观察组,各39例。对照组给予常规护理,观察组给予多元化干预联合零缺陷护理模式。比较两组Barthel指数、健康调查简表评分、并发症发生情况及护理满意度。结果:干预后,两组Barthel指数高于干预前,观察组高于对照组,差异有统计学意义(P<0.05);干预后,两组心理健康、社会功能、精力和躯体健康评分高于干预前,观察组高于对照组,差异有统计学意义(P<0.05);观察组并发症发生率低于对照组,差异有统计学意义(P=0.042);观察组护理满意度高于对照组,差异有统计学意义(P=0.025)。结论:多元化干预联合零缺陷护理模式能提高患者的生活活动能力及生活质量,降低并发症发生率,提高满意度。

基于多度量多模型图像投票的织物表面瑕疵检测方法

为解决自动化生产线上织物表面瑕疵检测准确率低和计算速度慢的问题,利用织物表面具有周期纹理的特性提出了一种改进的RANSac检测方法,即多度量多模型图像投票。首先将输入图像裁剪为尺寸一致的子图,计算出子图多维度量的输出值矩阵;然后与改进RANSac计算出的无瑕疵背景的多维度量标准值分别对应作差,采用投票得出每张子图的基础分;再将其在4个记数模型下得到的综合评分排序,根据顺序和偏移量在输出端得到外点所代表的瑕疵子图。实验结果表明:在自采样的织物瑕疵数据集上,选择单度量和单模型的预测精度平均可达到90.9%,平均预测时间达到0.139 s,综合多度量多模型投票的平均预测精度可达到92.7%。该算法不需要大量前期数据进行训练,适用于纯色和条纹状织物的实时表面缺陷检测。

共母线开绕组永磁同步牵引电机级联模型预测电流控制

为抑制共母线开绕组永磁同步牵引电机传动系统转矩脉动和由共模电压以及三次谐波反电动势作用于零轴回路产生的零序电流,提出一种自抗扰级联模型预测电流控制方法。首先,在第1级采用第1个有效电压矢量使得q轴电流增加,第2个有效电压矢量使得q轴电流减小,这一新的筛选组合规则将2个有效矢量根据对q轴电流作用效果分组寻优和作用时间分配;其次,在第2级对第1级所选有效电压矢量的零轴分量局部寻优,在第3级对第1级和第2级优化后系统产生的零轴电流分量采用极性相反的零矢量进行矢量分类寻优抑制,并精确分配作用时间;然后,在第4级对前3级所选电压矢量进行开关状态局部寻优,确定最优电压矢量的低开关频率状态组合作用于逆变器。最后,引入自抗扰控制减少电机启动加速过程中的调速超调,并对所提策略和双矢量模型预测电流控制进行稳态和动态仿真对比。结果表明:所提策略对转矩脉动、零轴电流、总谐波畸变率、开关频率和调速超调都具有很好的抑制效果,避免了传统模型预测控制的多目标代价函数中权重系数整定,对系统的控制性能有明显的提升作用。研究结果为进一步对共母线开绕组永磁同步牵引电机传动系统弱磁控制进行究,以及将驱动控制系统应用于机车牵引提供参考。

植被类型对晋南土壤入渗及地面水流糙率影响的研究

开展植被类型对土壤入渗特性及田面水流糙率影响的研究,可以为田间灌水技术参数的优化分析提供理论依据。以山西省夹马口引黄灌区试验站畦田灌水试验为依据,基于Kostiakov-Lewis三参数入渗模型,在运用水量平衡方程和曼宁公式的基础上,用单点求参法(用畦田内畦首、中、尾三点的入渗参数分别作为入渗参数值,仅对糙率值作优化求解)、均值求参法(用畦首、中、尾三点入渗参数的均值作为入渗参数值,仅对糙率值作优化求解)、组合求参法(用畦首、中、尾三点入渗参数中的最大值作为上限,最小值作为下限,对入渗参数和糙率值同时优化求解)对入渗参数及糙率进行直接求解,并利用基于零惯量模型的地面畦灌水流模拟软件WinSRFR4.1对求解参数进行了分析验证。结果表明:(1)用组合求参法拟合出的土壤入渗参数与地面水流糙率,决定系数R^(2)均在0.97以上,拟合精度较高。(2)玉米地土壤90 min累计入渗量Z_(90)为91.7 mm,糙率值为0.030;苹果树地Z_(90)为88.9 mm,糙率值为0.079;桃树地Z_(90)为115.9 mm,糙率值为0.138。在该试验区,一年生植物的Z_(90)明显大于多年生植物,植被类型对土壤入渗特性影响显著;鉴于组合求参法最大程度地弱化了土壤入渗参数的空间变异性,且拟合精度高于单点求参法和均值求参法,认为组合求参法最优,验证结果也进一步证明了该结论。

考虑锈蚀损伤的黏结滑移本构模型

为合理反映钢筋锈蚀后黏结滑移性能劣化对钢筋混凝土(RC)结构抗震性能的影响,在既有黏结应力分布模式的基础上,推导得到钢筋应力-滑移关系,进而通过分析锈蚀对混凝土与钢筋界面黏结滑移机理的影响,建立考虑钢筋锈蚀损伤的黏结滑移本构模型。基于已有拉拔试验结果,与仅考虑纵筋锈蚀率影响的Cheng模型进行对比,验证所建模型的合理性与准确性。基于OpenSees有限元平台,采用纤维梁柱单元和零长度截面单元串联的方式,将所建钢筋黏结滑移模型嵌套于零长度截面单元的钢筋本构中,建立可考虑黏黏结滑移的锈蚀损伤纤维梁柱模型,并通过6根锈蚀RC柱拟静力试验结果验证模型的准确性,结果发现所提考虑黏结滑移的锈蚀RC纤维梁柱模型计算所得滞回曲线与试验滞回曲线吻合良好,累计耗能最大误差不超过15%。此外,通过参数分析研究影响锈蚀钢筋滑移量的因素,结果表明屈服滑移量与极限滑移量随体积配箍率的增大而明显减小,随混凝土保护层与钢筋直径之比(c/d)增大而变化的幅度较小。