基于音频内容的混合域脆弱水印算法

提出一种用于内容认证的脆弱音频水印算法.与以往的脆弱音频水印算法相比,不采用二值图像作为脆弱水印,而是基于音频内容,利用奇异值分解生成脆弱水印.水印嵌入在离散小波变换和离散余弦变换构成的混合域.仿真实验表明,该算法具有很好的不可感知性,并且对有损压缩、添加噪声、重量化等操作具有很强的敏感性,同时能够对替换等恶意篡改做出报警并确定篡改位置.     

基于视频监控的铁路客运站人群密度分析算法

如何通过视频监控系统实时分析诸如广场、候车室等公共场所的人流密度变化,检测局部和整体人群是否过分拥挤,预防群体伤害事故,是目前研究的热点问题。为此,提出一种新算法进行人数估计,该算法具有较好的鲁棒性,可以适应复杂的背景和光照条件。     

格区间值Fuzzy集的分解定理(Ⅰ)

对格区间值Fuzzy集作了进一步的研究,分别给出了[λ1,λ2]、(λ1,λ2]、[λ1,λ2)、(λ1,λ2)上的下截集、上截集、下重截集和上重截集的新的定义及一种新的闭区间与格区间值Fuzzy集的运算,并给出了与此相应的四条重要的分解定理.     

基于小波变换的交通流数据集成灵敏度分析

道路上的交通流数据通常是以20-30秒间隔采集并传递到交通管理中心的，为了使这些数据能够广泛地运用于各种交通用途，必须采用合理高效的集成方法对其进行处理。传统的数据集成方法基于数理统计的理论，该方法不能有效地去除数据中的噪音。近年来迅速发展的基于小波变换的交通流数据集成方法克服了这一缺点，通过对交通流数据的频率特性进行详细分析能够使集成更加高效，准确满足不同的交通用途对集成的需求。但该方法尚未作进一步的灵敏度分析，本文通过对数据集成中小波函数和数据样本量这两个重要参数的分析，从理论的角度探讨了这两个参数变化对数据集成的影响。然后以北京市三环上的交通流数据为例，计算得到了数据集成建议采用的小波族和小波阶数，以及合理的最小样本量。该结论对数据集成在将来的实际应用具有指导意义。     

Wavelet Neural Network Based Traffic Prediction for Next Generation Network

By using netflow traffic collecting technology, some traffic data for analysis are collected from a next generation network （NGN） operator. To build a wavelet basis neural network （NN）, the Sigmoid function is replaced with the wavelet in NN. Then the wavelet multiresolution analysis method is used to decompose the traffic signal, and the decomposed component sequences are employed to train the NN. By using the methods, an NGN traffic prediction model is built to predict one day＇s traffic. The experimental results show that the traffic prediction method of wavelet NN is more accurate than that without using wavelet in the NGN traffic forecasting.     

Application of an improved EEMD method in bearing fault diagnosis of induction motors北大核心CSCD

[Objective]In order to overcome the disadvantages of the traditional ensemble empirical mode decomposition (EEMD) method in selecting parameters (integration time and white noise amplitude coefficient) based on experience, and reduce the cost of calculation time, a fast ensemble empirical mode decomposition (FEEMD) method is used to extract the characteristic frequency. [Method]By changing the distribution density of the added white noise, different signal envelopes can be obtained. Furthermore, we can identify the optimal envelope by finding the optimal search window width of the moving mean filter, thereby avoiding the defect of EEMD selecting parameters by experience. At the same time, after the abnormal component in the signal is decomposed, the residual component can be decomposed by EMD to further save the calculation time cost. Finally, the method is combined with Hilbert envelope demodulation technology and applied to the fault characteristic frequency diagnosis of the bearing inner ring of an asynchronous motor. [Results]As the results show, compared with the traditional EEMD method, FEEMD can extract the fault frequency more efficiently. [Conclusion]FEEMD overcomes the disadvantages of the traditional EEMD method in selecting parameters based on experience and shortens the calculation time. As such, it can be effectively applied in bearing fault frequency extraction experiments. © The Author(s) 2022.     

Comparison of road freight transport trends in Europe. Coupling and decoupling factors from an Input–Output structural decomposition analysis

Decoupling road freight transport from economic growth has been acknowledged by the European Union as a key means to improving sustainability. It is therefore important to identify both the coupling and decoupling drivers of road freight transport demand in order to determine possible factors that may contribute to reduce road transport in the future without curbing economic development. This research proposes an Input–Output (IO) structural decomposition analysis (SDA) to explain road freight transport in terms of a set of key factors that have strongly influenced road freight demand in recent decades in European countries—such as economic growth, economic structure and the evolution of road transport intensity (including improvements in both supply and transport systems). This methodological approach allows us to quantify and compare their contribution in different European countries to either increase or decrease road freight transport demand. The empirical basis for this analysis is a dataset of nine European countries which have IO tables and road transport data available from 2000 to 2007, comprising data on domestic production, imports and exports as well as tonne-kms for 11 types of commodity classes. The results show that, as a whole, aggregate road transport demand has grown—driven mainly by economic activity—but this growth has been strongly curbed in some countries by changes in road freight transport intensity and moderately by the dematerialization of the economy. International transport has been also proven to be a key factor driving road freight transport volumes. Moreover, the increased penetration of foreign operators in national haulage markets appears to have reinforced the final decoupling levels observed in some cases.     

THEORY AND APPLICATION OF M-BAND WAVELET TRANSFORM

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Model and a solution algorithm for the dynamic resource allocation problem for large-scale transportation network evacuation

Allocating movable resources dynamically enables evacuation management agencies to improve evacuation system performance in both the spatial and temporal dimensions. This study proposes a mixed integer linear program (MILP) model to address the dynamic resource allocation problem for transportation evacuation planning on large-scale networks. The proposed model is built on the earliest arrival flow formulation that significantly reduces problem size. A set of binary variables, specifically, the beginning and the ending time of resource allocation at a location, enable a strong formulation with tight constraints. A solution algorithm is developed to solve for an optimal solution on large-scale network applications by adopting Benders decomposition. In this algorithm, the MILP model is decomposed into two sub-problems. The first sub-problem, called the restricted master problem, identifies a feasible dynamic resource allocation plan. The second sub-problem, called the auxiliary problem, models dynamic traffic assignment in the evacuation network given a resource allocation plan. A numerical study is performed on the Dallas–Fort Worth network. The results show that the Benders decomposition algorithm can solve an optimal solution efficiently on a large-scale network.     

到球面上的四维非齐次双调和映射连续性

对到球面上的四维非齐次双调和映射,本文根据球面的几何结构和四维Lorentz空间的特殊性,得到了在Lorentz空间的估计式,从而得到其弱解的连续性结果.