提出一种分析头相关传输函数(head-related transfer function,HRTF)幅度谱的听觉空间分辨阈值模型。采用数值计算得到的高空间分辨率HRTF数据,计算了声源空间位置变化引起的HRTF幅度谱的变化,进一步利用Moore响度模型分析双耳响度级差...提出一种分析头相关传输函数(head-related transfer function,HRTF)幅度谱的听觉空间分辨阈值模型。采用数值计算得到的高空间分辨率HRTF数据,计算了声源空间位置变化引起的HRTF幅度谱的变化,进一步利用Moore响度模型分析双耳响度级差、双耳响度级谱和总响度级等三个听觉感知量的变化。根据现有的3个听觉感知量最小可察觉差异,模型利用双耳响度级差和双耳响度级谱的变化得到的估计结果与心理声学实验一致,因此是一种有效预测听觉空间分辨阈值的方法,可用于为简化虚拟听觉信号处理和数据储存。展开更多
This paper uses Covasim,an agent-based model(ABM)of COVID-19,to evaluate and scenarios of epidemic spread in New York State(USA)and the UK.Epidemiological parameters such as contagiousness(virus transmission rate),ini...This paper uses Covasim,an agent-based model(ABM)of COVID-19,to evaluate and scenarios of epidemic spread in New York State(USA)and the UK.Epidemiological parameters such as contagiousness(virus transmission rate),initial number of infected people,and probability of being tested depend on the region's demographic and geographical features,the containment measures introduced;they are calibrated to data about COVID-19 spread in the region of interest.At the first stage of our study,epidemiological data(numbers of people tested,diagnoses,critical cases,hospitalizations,and deaths)for each of the mentioned regions were analyzed.The data were characterized in terms of seasonality,stationarity,and dependency spaces,and were extrapolated using machine learning techniques to specify unknown epidemiological parameters of the model.At the second stage,the Optuna optimizer based on the tree Parzen estimation method for objective function minimization was applied to determine the model's unknown parameters.The model was validated with the historical data of 2020.The modeled results of COVID-19 spread in New York State and the UK have demonstrated that if the level of testing and containment measures is preserved,the number of positive cases in New York State remain the same during March of 2021,while in the UK it will reduce.展开更多
文摘提出一种分析头相关传输函数(head-related transfer function,HRTF)幅度谱的听觉空间分辨阈值模型。采用数值计算得到的高空间分辨率HRTF数据,计算了声源空间位置变化引起的HRTF幅度谱的变化,进一步利用Moore响度模型分析双耳响度级差、双耳响度级谱和总响度级等三个听觉感知量的变化。根据现有的3个听觉感知量最小可察觉差异,模型利用双耳响度级差和双耳响度级谱的变化得到的估计结果与心理声学实验一致,因此是一种有效预测听觉空间分辨阈值的方法,可用于为简化虚拟听觉信号处理和数据储存。
基金supported by the Russian Foundation for Basic Research and Royal Society(project no.21-51-10003)The agent-based mathematical model construction and analysis of numerical results(sections 3,4,5)+1 种基金supported by the Russian Science Foundation(project no.18-71-10044)the Royal Society IECyR2y202020 e International Exchanges 2020 Cost Share between UK and Russia.
文摘This paper uses Covasim,an agent-based model(ABM)of COVID-19,to evaluate and scenarios of epidemic spread in New York State(USA)and the UK.Epidemiological parameters such as contagiousness(virus transmission rate),initial number of infected people,and probability of being tested depend on the region's demographic and geographical features,the containment measures introduced;they are calibrated to data about COVID-19 spread in the region of interest.At the first stage of our study,epidemiological data(numbers of people tested,diagnoses,critical cases,hospitalizations,and deaths)for each of the mentioned regions were analyzed.The data were characterized in terms of seasonality,stationarity,and dependency spaces,and were extrapolated using machine learning techniques to specify unknown epidemiological parameters of the model.At the second stage,the Optuna optimizer based on the tree Parzen estimation method for objective function minimization was applied to determine the model's unknown parameters.The model was validated with the historical data of 2020.The modeled results of COVID-19 spread in New York State and the UK have demonstrated that if the level of testing and containment measures is preserved,the number of positive cases in New York State remain the same during March of 2021,while in the UK it will reduce.
