基于Shadowing模型的无线入侵主机物理定位研究

为了在室内无线局域网环境中及时准确地定位非法入侵主机物理位置,以无线信号强度衰减过程的Shadowing传播模型为基础,研究了在一定的范围内如何合理地布置探测器,如何根据接收到的入侵主机的信号强度进行物理定位的问题.提出的定位方法可以有效地对抗入侵主机随机更改信号发射功率对定位精度的影响.实际测试结果表明,该方法定位误差平均约为2.3 m,可以满足室内环境下定位非法入侵主机的需求.

Inhomogeneous Shadowing Effect in High-Energy p-A Drell-Yan Process:

Having studied the initial state energy loss versus nuclear shadowing for the Drell-Yan dimuon pairproduction in the color string model,the inhomogeneous shadowing effect is considered in this paper.We find thatthe inhomogeneous shadowing effect does amend the rate of energy loss per unit path length,-dE/dz.Finally,thetheoretical results for the Drell-Yan differential cross-section ratios are compared with the E772 and E866 data.It isfound that the theoretical results are in good agreement with the experimental data.

An efficient approach for shadow detection based on Gaussian mixture model

An efficient approach was proposed for discriminating shadows from moving objects. In the background subtraction stage, moving objects were extracted. Then, the initial classification for moving shadow pixels and foreground object pixels was performed by using color invariant features. In the shadow model learning stage, instead of a single Gaussian distribution, it was assumed that the density function computed on the values of chromaticity difference or bright difference, can be modeled as a mixture of Gaussian consisting of two density functions. Meanwhile, the Gaussian parameter estimation was performed by using EM algorithm. The estimates were used to obtain shadow mask according to two constraints. Finally, experiments were carried out. The visual experiment results confirm the effectiveness of proposed method. Quantitative results in terms of the shadow detection rate and the shadow discrimination rate(the maximum values are 85.79% and 97.56%, respectively) show that the proposed approach achieves a satisfying result with post-processing step.

Precise Asymptotic Distribution of the Number of Isolated Nodes in Wireless Networks with Lognormal Shadowing

In this paper, we study the connectivity of multihop wireless networks under the log-normal shadowing model by investigating the precise distribution of the number of isolated nodes. Under such a realistic shadowing model, all previous known works on the distribution of the number of isolated nodes were obtained only based on simulation studies or by ignoring the important boundary effect to avoid the challenging technical analysis, and thus cannot be applied to any practical wireless networks. It is extremely challenging to take the complicated boundary effect into consideration under such a realistic model because the transmission area of each node is an irregular region other than a circular area. Assume that the wireless nodes are represented by a Poisson point process with densitynover a unit-area disk, and that the transmission power is properly chosen so that the expected node degree of the network equals lnn + ξ (n), where ξ (n) approaches to a constant ξ as n →?∞. Under such a shadowing model with the boundary effect taken into consideration, we proved that the total number of isolated nodes is asymptotically Poisson with mean e$ {-ξ}. The Brun’s sieve is utilized to derive the precise asymptotic distribution. Our results can be used as design guidelines for any practical multihop wireless network where both the shadowing and boundary effects must be taken into consideration.

Linear Maximum Likelihood Regression Analysis for Untransformed Log-Normally Distributed Data

Medical research data are often skewed and heteroscedastic. It has therefore become practice to log-transform data in regression analysis, in order to stabilize the variance. Regression analysis on log-transformed data estimates the relative effect, whereas it is often the absolute effect of a predictor that is of interest. We propose a maximum likelihood (ML)-based approach to estimate a linear regression model on log-normal, heteroscedastic data. The new method was evaluated with a large simulation study. Log-normal observations were generated according to the simulation models and parameters were estimated using the new ML method, ordinary least-squares regression (LS) and weighed least-squares regression (WLS). All three methods produced unbiased estimates of parameters and expected response, and ML and WLS yielded smaller standard errors than LS. The approximate normality of the Wald statistic, used for tests of the ML estimates, in most situations produced correct type I error risk. Only ML and WLS produced correct confidence intervals for the estimated expected value. ML had the highest power for tests regarding β1.

Distance Measurement Model Based on RSSI in WSN

The relationship between RSSI (Received Signal Strength Indication) values and distance is the foundation and the key of ranging and positioning technologies in wireless sensor networks. Log-normal shadowing model (LNSM), as a more general signal propagation model, can better describe the relationship between the RSSI value and distance, but the parameter of variance in LNSM is depended on experiences without self-adaptability. In this paper, it is found that the variance of RSSI value changes along with distance regu- larly by analyzing a large number of experimental data. Based on the result of analysis, we proposed the relationship function of the variance of RSSI and distance, and established the log-normal shadowing model with dynamic variance (LNSM-DV). At the same time, the method of least squares(LS) was selected to es- timate the coefficients in that model, thus LNSM-DV might be adjusted dynamically according to the change of environment and be self-adaptable. The experimental results show that LNSM-DV can further reduce er- ror, and have strong self-adaptability to various environments compared with the LNSM.

Downlink BER performance analysis of distributed antenna systems over shadowed Rayleigh fading channels

Due to the complexity of the composite fading channel, a new simplified channel model is proposed to analyze the bit error ratio（BER） performance of the distributed antenna system （DAS）. First, instead of the gamma-log-normal distribution, the log-normal distribution is applied to describe the output signal to noise ratio（SNR） after maximal ratio combining （MRC） at the receiver. Then, assuming that the channel state information（CSI） is available to the transmitter, by employing the Gauss-Hermite integral, an approximate analytical expression of the BER is derived for the downlink of the DAS with antenna selective transmission and MRC. Finally, the results of a Monte Carlo simulation show that the analytical results match the simulation results. Therefore, it can be concluded that the proposed approximate channel model is effective and accurate, and the derived analytical expression can be used to evaluate the real system performance.

A General Channel Model for Visible Light Communications in Underground Mines

In underground mines, visible light communication(VLC) system is a promising method to realize effective communication,which supports communication and illumination at the same time. Therefore, adequate research of underlying physical propagation phenomenon should be carried out to realize VLC system in underground mines. To design VLC system and evaluate its performance, accurate and efficient channel models, including large-scale fading and scattering characteristics, are needed to be established. However,the characteristics of the underlying VLC channels about fading and scattering have not been sufficiently investigated yet. In this paper, a path loss channel model, based on the recursive model, is proposed precisely. Its path loss exponent is determined by three different trajectories, which is studied in the mining roadway and working face environment. Besides, the shadowing effect for VLC has been modelled by a Bimodal Gaussian distribution in underground mines. Considering the number of transmitters in line-of-sight(Lo S) as well as non-line-of-sight(NLo S) scenarios,our simulation illustrates the fact that, as the curve fitting technique is employed, the path loss displays a linear behavior in log-domain.The path loss expression is derived, it is related to the distance. Finally, root mean square(RMS) delay spread and Mie scattering in underground mines are analyzed.

Improvement of Glacial Lakes Detection under Shadow Environment Using ASTER Data in Himalayas, Nepal

The detection of glacial lake change in the Himalayas, Nepal is extremely significant since the glacial lake change is one of the crucial indicators of global climate change in this area, where is the most sensitive area of the global climate changes. In the Hima- layas, some of glacial lakes are covered by the dark mountains＇ shadow because of their location. Therefore, these lakes can not be de- tected by conventional method such as Normalized Difference Water Index （NDWI）, because the reflectance feature of shadowed glacial lake is different comparing to the ones which are located in the open flat area. The shadow causes two major problems： 1） glacial lakes which are covered by shadow completely result in underestimation of the number of glacial lakes; 2） glacial lakes which are partly iden- tified are considered to undervalue the area of glacial lakes. The aim of this study is to develop a new model, named Detection of Shadowed Glacial Lakes （DSGL） model, to identify glacial lakes under the shadow environment by using Advanced Space-borne Ther- mal Emission and Reflection Radiometer （ASTER） data in the Himalayas, Nepal. The DSGL model is based on integration of two dif- ferent modifications of NDWI, namely NDWls model and NDWIshe model. NDWI~ is defined as integration of the NDWI and slope analysis and used for detecting non-shadowed lake in the mountain area. The NDWIshe is proposed as a new methodology to overcome the weakness of NDWI~ on identifying shadowed lakes in highly elevated mountainous area such as the Himalayas. The first step of the NDWIshe is to enhance the data from ASTER 1B using the histogram equalization （HE） method, and its outcome product is named AS- TERho. We used the ASTERhe for calculating the NDWIhc and the NDWIshe. Integrated with terrain analysis using Digital Elevation Model （DEM） data, the NDWIshe can be used to identify the shadowed glacial lakes in the Himalayas. NDWIs value of 0.41 is used to identify the glacier lake （NDWI~ 〉 0.41）, and 0.3 of NDWIshe is used to identify the shadowed glacier lake （NDWIsho 〈 0.3）. The DSGL model was proved to be able to classify the glacial lakes more accurately, while the NDWI model had tendency to underestimate the presence of actual glacial lakes. Correct classification rate regarding the products from NDWI model and DSGL model were 57% and 99%, respectively. The results of this paper demonstrated that the DSGL model is promising to detect glacial lakes in the shadowed en- vironment at high mountains.

A NEW METHOD OF MOVING OBJECT DETECTION AND SHADOW REMOVING

This paper presents an adaptive method of objects and shadows detection in video streams. Models of background are firstly set up and adaptively updated in Hue Saturation Intensity (HSI) color space to detect motion regions. Then, detection errors are dealt with by motion continuity and velocity consistency. Finally, cast shadows are removed by the generic properties of luminance, chrominance and gradient density. Experimental results and their evaluation are presented to verify the effectiveness of this new method.

A time fractional model to represent rainfall process

This paper deals with a stochastic representation of the rainfall process. The analysis of a rainfall time series shows that cumulative representation of a rainfall time series can be modeled as a non-Gaussian random walk with a log-normal jump distribution and a time-waiting distribution following a tempered a-stable probability law. Based on the random walk model, a fractional Fokker-Planck equation （FFPE） with tempered a-stable waiting times was obtained. Through the comparison of observed data and simulated results from the random walk model and FFPE model with tempered a-stable waiting times, it can be concluded that the behavior of the rainfall process is globally reproduced, and the FFPE model with tempered a-stable waiting times is more efficient in reproducing the observed behavior.

CONTINUOUS THERMODYNAMICS FOR POLYMER SOLUTIONS I.CLOSE-PACKED LATTICE MODEL

using close-packed lattice models,a continuous thermodynamic framework is presented forphase-equilibrium calculations for binary solutions with a polydisperse polymer solute.An expressionfor the Helmholtz function of mixing is based on the revised Freed model developed previously.Asize parameter c_r and an energy parameter ε are used;the former can be temperature dependent,while the latter can depend on both temperature and chain-length of the polymer.The discretemulticomponent approach is adopted to derive expressions for chemical potentials,spinodals and criti-cal points.The continuous distribution function is then used in calculations of moments occurring inthose expressions.Computation programs are established for cloud-point-curve,shadow-curve,spinodal and critical-point calculations for polymer solutions with standard distribution or arbitrarydistribution of polymer.In the latter case,the derivative method developed previously is applied.lllustrations for phase-equilibrium calculations are

Application of Dual Model to Animal Feed Formulation Optimizing System

This study introduced a dual model on an original linear programming to obtain those shadow prices of resources that take part in optimizing. Of feed formulation, the shadow prices of nutrient resources show their influencing degree on a diet last cost when increasing or decreasing expected diet nutrient values. The higher the shadow price of one nutrient resource, the more obvious its influencing action on a diet last cost. When the shadow price of a kind of resource equals 'zero', it means that reaching of this nutrient value does not have influence on a special diet last cost within a particular value range. At the same time, this paper discussed the future development direction of feed formulation optimizing techniques in China.

CONTINUOUS THERMODYNAMICS FOR POLYMER SOLUTIONS II . LATTICE FLUID MODEL

Using lattice-fluid model, a continuous thermodynamic framework is presented for phase-equilibrium calculations for binary solutions with a polydisperse polymer solute. A two-step process is designed to form a real polymer solution containing a solvent and a polydisperse polymer solute occupying a volume at fixed temperature and pressure. In the first step, close-packed pure components including solvent and polymers with different molar masses or different chain lengths are mixed to form a closed-packed polymer solution. In the second step, the close-packed mixture, considered to be a pseudo-pure substance is mixed with holes to form a real polymer solution with a volume dependent on temperature and pressure. Revised Freed's model developed previously is adopted for both steps. Besides pure-component parameters, a binary size parameter cr and a binary energy parameter e12 are used. They are all temperature dependent. The discrete-multicomponent approach is adopted to derive expressions for chemical potentials, spinodals and critical points. The continuous distribution function is then used in calculations of moments occurring in those expressions. Computation procedures are established for cloud-point-curve, shadow-curve, spinodal and critical-point calculations using standard distribution or arbitrary distribution on molar mass or on chain length. Illustrative examples are also presented.

Performance Analysis of a DS-CDMA Cellular System with Effects of Soft Handoff in Log-Normal Shadowing Channels

Next generation wireless communication is based on a global system of fixed and wireless mobile services thatare transportable across different network back-bones,network service providers and network geographical boundaries.This paper presents an approach to investigate the effects of soft handover and perfect power control on the forward link ina DS-CDMA cellular system.Especially,the relationships between the size ofhandover zone and the capacity gain are e-valuated under the log-normal shadow channel.Then the optimization of maximum forward capacity is very necessary tobe done with the maximum size of soft handover zone to the various system characteristics.

QoS Aware Routing Protocol to Improve Packet Transmission in Shadow-Fading Environment for Mobile Ad Hoc Networks

In Shadow-Fading model, it is difficult to achieve higher Packet Delivery Ratio (PDR) due to the effects of large scale fading. The main goal of this paper is to improve the PDR in Shadow-Fading environment. To achieve this objective a protocol has been proposed that discovers backup routes for active sessions. These backup routes salvage the packets of active session in case of active route failure. It is found by research that proactively maintaining backup routes for ac-tive sessions can noticeably improve the PDR in Shadow-Fading environment. This protocol has been implemented with a mechanism of having backup routes and simulations have been conducted by using both node disjoint paths and link disjoint paths. Comparisons have been made between new protocol as well as AODV protocol. Simulation has been carried out using Network Simulator 2 (NS2) and the results show that the proposed QoSAR protocol exhibits higher PDR than AODV protocol in Shadow-fading environment.

上市公司影子银行化对金融稳定的影响与机制研究

影子银行因其规模的日益扩大及其带来的巨大影响而受到政府与学术界的广泛关注。本文基于上市公司财务数据和金融稳定相关数据,运用CRITIC指数构建法和误差修正模型,对上市公司影子银行化对金融稳定的影响与机制进行了理论分析与实证检验。研究发现:上市公司影子银行化提高了经济金融化程度,进而增加金融脆弱性而影响金融稳定。金融稳定更多受到东部、中部地区上市公司影子银行化的影响。相较于规模较小与盈利能力较弱上市公司,规模较大上市公司与盈利能力较强上市公司影子银行化对金融稳定造成的影响更大。研究结果有助于深化影子银行发展对金融稳定影响的理解,对强化上市公司金融化行为监管,维护金融稳定,实现金融高质量发展具有重要的政策意义。

“断层阴影”识别与校正方法——以松辽盆地升平构造为例

地层错断往往引起速度横向突变,导致在时间域地震资料中出现“断层阴影”现象,影响地质解释结果及圈闭评价等。为此,以松辽盆地升平构造为例,分析“断层阴影”现象,提出了正演模拟法、井震结合地层对比法和平均速度成图法三种识别方法;在此基础上,针对“断层阴影”,提出了高精度速度场校正和时间域层位校正两种校正方法。结果表明,高精度速度场校正法可以实现数据体的校正,适应性更广;时间域层位校正法可以实现层位的校正,具有快速、简便的优势。该方法对类似地区具有借鉴意义。

以全球导航卫星系统为辐射源的前向散射雷达发展综述

前向散射雷达(FSR)可获得高水平雷达截面积(RCS)的特性使其在反隐身中占据重要地位。利用全球导航卫星系统(GNSS)作为辐射源,具有全天时全天候全地域覆盖的优势,通过部署多个接收节点可构建地面/海上/空中目标监视网络。该文针对基于GNSS的FSR发展现状,从目标检测、目标参数估计、阴影逆合成孔径雷达(SISAR)成像及目标分类识别等方面对关键技术和现存问题进行概述,并从组网探测、多目标定位、布站优化和极化信息获取等方面对基于GNSS的FSR发展趋势提出展望。

Black-box membership inference attacks based on shadow model

Membership inference attacks on machine learning models have drawn significant attention.While current research primarily utilizes shadow modeling techniques,which require knowledge of the target model and training data,practical scenarios involve black-box access to the target model with no available information.Limited training data further complicate the implementation of these attacks.In this paper,we experimentally compare common data enhancement schemes and propose a data synthesis framework based on the variational autoencoder generative adversarial network(VAE-GAN)to extend the training data for shadow models.Meanwhile,this paper proposes a shadow model training algorithm based on adversarial training to improve the shadow model's ability to mimic the predicted behavior of the target model when the target model's information is unknown.By conducting attack experiments on different models under the black-box access setting,this paper verifies the effectiveness of the VAE-GAN-based data synthesis framework for improving the accuracy of membership inference attack.Furthermore,we verify that the shadow model,trained by using the adversarial training approach,effectively improves the degree of mimicking the predicted behavior of the target model.Compared with existing research methods,the method proposed in this paper achieves a 2%improvement in attack accuracy and delivers better attack performance.