开放式办公室声环境评价、预测和设计方法

开放武办公室作为一种应用广泛的办公场所，其内部声环境研究具有重要的意义。目前，国际上的研究主要围绕语言私密度问题展开。综述了私密度评价指标及获取方法、开放式办公室建模预测方法和声学设计等方面的研究进展。     

开放式办公室内部声场计算机模拟

介绍了几种常用的建筑声学模拟软件,并通过实例研究了ODEON软件在开放式办公室内部声场特性分析中的应用。     

稳态响度听觉原理及A计权声级评价的缺点

A计权声级和响度是噪声评价的两种方法。通过对响度计算原理的分析，对比分析出A计权声级在度量低频成分为主的噪声、离散噪声和语音频率范围噪声时会产生误差，使评价结果偏离人的主观感觉。指出要对噪声信号进行深入分析，采用响度评价更科学。     

防空信息战系统的灰色层次评价模型

针对防空信息战的特点，建立了评价指标体系。同时，将灰色关联分析与层次分析相结合．提出了灰色层次关联分析，并对防空信息战系统的效能评价进行了研究，给出了一种多指标评价的方法。该方法利用了待评方案的离差最大化原则和最大熵原理，建立了防空信息战系统的灰色层次关联评价模型。最后，通过实例计算表明模型的实用性和价值。     

基于大数据的地方电网电能量采集系统量化评价体系研究

随着大数据时代的到来，以及发展智能电网的计划和理念，电网用户采集系统也扮演着十分重要的角色，其应用效果评估体系有助于综合衡量各电网用采系统水平，为项目建设提供指导意见。本文首先给出用采系统量化评价相关的基础理论，然后以技术、经济、管理以及社会效益四大类指标为研究对象，细分23类子指标，并给出指标赋值方法。最后基于大数据技术，结合熵值法与灰色理论对地方电网用采系统建立量化评价体系，给出案例分析。通过5个公司的案例，利用客观的熵值法赋权，通过灰色关联分析法计算5家公司23个指标的关联系数，计算得5个公司综合得分分别为：60.9%，66.5%，61.4%，57.6%和56.9%，评价排名为：B公司>C公司>A公司>D公司> E公司。本文的研究结果不仅可以提供各地方电网用采水平排名，也能为电网进一步建设和改进用采系统提供建议。     

基于灰色关联投影法的飞机生存力设计方案评估

分析了飞机生存力设计方案的评价指标集并赋给每个指标不同的权重系数，提出了一种基于灰色关联投影法的飞机生存力设计方案评估方法。该方法采用灰色关联理论建立各生存力设计方案对评价指标集的加权灰色关联判断矩阵，然后利用矢量投影原理计算了各设计方案相对理想方案的灰色关联投影值，根据灰色关联投影值可以评价设计方案的优劣。     

《邮电通信建设项目经济评价方法与参数（第二版）》说明和解析（二）

首先阐述了建立邮电通信建设项目财务评价指标体系的必要性，可能性和指标体系的结构及各部分的作用，比较系统地介绍了各项评价指标的含义，计算方法，优缺点及其使用时需要注意的问题；指出了财务评价指标的判别方法和判据；最后说明了各项财务评价指标与财务基本报表的对应关系。     

用相对热指标和预测平均反应研究火车站热舒适状况

介绍了稳态和过渡空间下室内热舒适性的评价指标,对西安火车站候车厅热环境参数进行了现场测试,并用RWI和PMV．PPD两个指标对测试环境的热舒适性进行分析计算和评价,认为RWI指标更适合评价火车站热舒适。     

信号交叉口微观仿真系统评价指标分析

对仿真系统的交通运行评价可以反映仿真系统模拟的准确性和控制结果的有效性.通过对交叉口车辆运行评价指标的关联性分析,建立了行车延误、平均排队长度、平均停车次数、二次排队率等4个相对独立有效的交叉口仿真系统运行评价指标.在对各评价指标的仿真属性分析的基础上提出了系统中评价指标的计算方法与具体实现原理.     

基于模糊理论的光成像技术网络课程质量评价系统

由于光成像技术网络课程质量评价指标难以准确量化，评价精度低，为此利用模糊理论分别从多个方面实现对光成像技术网络课程质量评价系统的优化设计。在硬件方面，采用新型或改装的存储器、接口芯片以及中央处理器来代替传统的硬件设备，并对通信网络和电路的连接方式进行改装。通过分析光成像技术网络课程特点，建立数据库及数据库表。在硬件设备和数据库的双重支持下，通过分析确定光成像技术网络课程质量评价内容和评价指标，并利用模糊理论实现评价指标的模糊求解，通过指标与权重的计算处理得出最终的质量评价结果。与传统评价系统的对比得出结论：通过模糊理论的应用，系统的评价误差有所降低，在光成像技术网络课程质量评价的精度方面更加具有优势。     

声表面波小波处理器的计算机模拟与仿真

由于缺乏基本的计算机模拟与仿真手段,我们无法在试制样品前预估所设计的声表面波小波处理器的性能参数。因而,一旦设计参数出现偏差,所试制的样品的性能指标也就不可能满足设计要求,这不但延长研发周期,而且浪费大量不必要的研发经费。为此,该文介绍了一种对声表面波小波处理器进行计算机模拟与仿真的模型,并将其用于声表面波小波处理器的设计研制中,以期在样品试制前对其进行计算机模拟与仿真,直至模拟与仿真结果满足设计要求后再进行样品试制与测试,以尽可能地缩短研究周期,节约研究经费。理论与研究结果表明,采用该文介绍的计算机模拟与仿真模型对声表面波小波处理器进行计算机模拟与仿真,其模拟仿真结果与实测结果相比,其误差小于1%,基本能满足设计研发工作的需要。     

一种任务域无关的语音关键词检测系统

提出了面向语音关键词检测的多尺度声学模型建模框架,基于判决树的自动音素聚类生成了大尺度音素集,利用HMM声学模型训练技术生成了大尺度音素声学上下文相关的背景模型,提高了废料语音的建模精度,还给出了此框架下共享HMM状态的高效搜索空间构造方法,关键词识别准确率平均提高了绝对6.9%;提出了近邻声学上下文准则以及候选关键词在多尺度声学模型上的似然比计算方法并采用FLDA融合,显著提高了声学置信度计算的有效性,系统等错率绝对下降了3.0%。     

Analysis of Acoustic Signatures from Moving Vehicles Using Time-Varying Autoregressive Models

Time-varying autoregressive (TVAR) modeling approach for the analysis of acoustic signatures from moving vehicles is presented in this paper. Acoustic signatures from moving vehicles are nonstationary, and features extracted under the stationary assumption often result unsatisfactory performance. In TVAR modeling approach, the time-varying parameters are expanded as a linear combination of deterministic time functions. In this paper, the TVAR parameters are expanded by a low-order discrete cosine transform (DCT), since DCT is known to be close to the optimal Kahrunen-Loève transform when the signal is Markov. The maximum likelihood estimation and order selection in TVAR models are also discussed. Many attributes of vehicle activities, such as vehicle type, engine speed, loading, road condition, etc., may be inferred from the estimated model parameters. The performance of the TVAR modeling approach is tested with both synthetic and real acoustic signatures. A synthetic signal containing multiple time-varying sinusoids are used to compare the performances in the estimation of time-frequency distribution with other approaches. In the experiment with acoustic signatures from moving vehicles, it is shown that the TVAR models can be effectively used to determine vehicle activities and types at close range and cruising speed.     

Acoustic FMRI noise: linear time-invariant system model

Functional magnetic resonance imaging (fMRI) enables sites of brain activation to be localized in human subjects. For auditory system studies, however, the acoustic noise generated by the scanner tends to interfere with the assessments of this activation. Understanding and modeling fMRI acoustic noise is a useful step to its reduction. To study acoustic noise, the MR scanner is modeled as a linear electroacoustical system generating sound pressure signals proportional to the time derivative of the input gradient currents. The transfer function of one MR scanner is determined for two different input specifications: 1) by using the gradient waveform calculated by the scanner software and 2) by using a recording of the gradient current. Up to 4 kHz, the first method is shown as reliable as the second one, and its use is encouraged when direct measurements of gradient currents are not possible. Additionally, the linear order and average damping properties of the gradient coil system are determined by impulse response analysis. Since fMRI is often based on echo planar imaging (EPI) sequences, a useful validation of the transfer function prediction ability can be obtained by calculating the acoustic output for the EPI sequence. We found a predicted sound pressure level (SPL) for the EPI sequence of 104 dB SPL compared to a measured value of 102 dB SPL. As yet, the predicted EPI pressure waveform shows similarity as well as some differences with the directly measured EPI pressure waveform.      

Model selection of random amplitude polynomial phase signals

Procedures for selecting the amplitude and phase models of a polynomial phase signal (PPS) modulated by a nonstationary random process are presented. The model selection is performed by using nonlinear least-squares type phase and amplitude parameter estimators with sequential generalizations of the Bonferroni test. Simulation results are used to analyze the performance of the procedures. An application to modeling of real passive acoustic data is presented     

Application research of optical communication network based on artificial intelligence technique

The applications of artificial intelligence (AI) technique in optical communication networks were explored.Some representative AI applications and potential risks due to the failure of the AI technique were discussed.To address these risks,methods including systematic AI modeling through unitizing and miniaturizing sub-systems and cooperation with traditional network modeling and planning methods were proposed,which were expected to help improve the effectiveness and practicality of the application of the AI technique.Finally,to recover a system from the failure of its employed AI technique or attacks,some protection strategies were proposed.     

Modeling of noncollinear multifrequency acoustooptic interaction inguided-wave Bragg cells

We present an original detailed theoretical modeling of guided-wave noncollinear acoustooptic (AO) interaction produced by a multifrequency surface acoustic wave (SAW) in planar guided-wave structures. The modeling of the multifrequency AO interaction is based on a modified version of the coupled-mode theory. The first- and third-order diffraction efficiency and optimum dynamic range of the Bragg cell have been calculated as a function of acoustic power, acoustic radiofrequency, and optical waveguide parameters in Y-cut Ti:LiNbO₃ planar waveguides. Polynomial approximations, describing the first and third order diffraction efficiency versus normalized acoustic power in the cases of two- and three-frequency interactions, are derived and presented for the first time for arbitrarily large RF signals     

The Layout of Post Offices in a New Area of a City

An analysis on the factors which affect the layout of post offices is made. Research on the laws of distribution of post offices in cities is done. The method of determining the number of post offices and the layout of post offices in a new area of a city are put forward in this paper.     

Public perceptions on artificial intelligence driven disaster management: Evidence from Sydney,Melbourne and Brisbane

In recent years, artificial intelligence (AI) is being increasingly utilised in disaster management activities. The public is engaged with AI in various ways in these activities. For instance, crowdsourcing applications developed for disaster management to handle the tasks of collecting data through social media platforms, and increasing disaster awareness through serious gaming applications. Nonetheless, there are limited empirical investigations and understanding on public perceptions concerning AI for disaster management. Bridging this knowledge gap is the justification for this paper. The methodological approach adopted involved: Initially, collecting data through an online survey from residents (n = 605) of three major Australian cities; Then, analysis of the data using statistical modelling. The analysis results revealed that: (a) Younger generations have a greater appreciation of opportunities created by AI-driven applications for disaster management; (b) People with tertiary education have a greater understanding of the benefits of AI in managing the pre- and post-disaster phases, and; (c) Public sector administrative and safety workers, who play a vital role in managing disasters, place a greater value on the contributions by AI in disaster management. The study advocates relevant authorities to consider public perceptions in their efforts in integrating AI in disaster management.