Critical behavior of the Gaussian model on fractal lattices in external magnetic field

For inhomogeneous lattices we generalize the classical Gaussian model, i.e. it is proposed that the Gaussian type distribution constant and the external magnetic field of site i in this model depend on the coordination number qi of site i, and that the relation $b_{q_i}/b_{q_j} = q{_i}/q{_j}$ holds among bq's, where bq is the Gaussian type distribution constant of site j. Using the decimation real-space renormalization group following the spin-rescaling method, the critical points and critical exponents of the Gaussian model are calculated on some Koch type curves and a family of the diamond-type hierarchical (or DH) lattices. At the critical points, it is found that the nearest-neighbor interaction and the magnetic field of site j can be expressed in the form $K^* = b{_q }_{_i } /q{_i } and h_{q_j }^* = 0$ respectively. It is also found that most critical exponents depend on the fractal dimensionality of a fractal system. For the family of the DH lattices, the results are identical with the exact results on translation symmetric lattices, and if the fractal dimensionalityd f=4, the Gaussian model and the mean field theories give the same results.

Non-Gaussian Lagrangian Stochastic Model for Wind Field Simulation in the Surface Layer

Wind field simulation in the surface layer is often used to manage natural resources in terms of air quality,gene flow(through pollen drift),and plant disease transmission(spore dispersion).Although Lagrangian stochastic(LS)models describe stochastic wind behaviors,such models assume that wind velocities follow Gaussian distributions.However,measured surface-layer wind velocities show a strong skewness and kurtosis.This paper presents an improved model,a non-Gaussian LS model,which incorporates controllable non-Gaussian random variables to simulate the targeted non-Gaussian velocity distribution with more accurate skewness and kurtosis.Wind velocity statistics generated by the non-Gaussian model are evaluated by using the field data from the Cooperative Atmospheric Surface Exchange Study,October 1999 experimental dataset and comparing the data with statistics from the original Gaussian model.Results show that the non-Gaussian model improves the wind trajectory simulation by stably producing precise skewness and kurtosis in simulated wind velocities without sacrificing other features of the traditional Gaussian LS model,such as the accuracy in the mean and variance of simulated velocities.This improvement also leads to better accuracy in friction velocity(i.e.,a coupling of three-dimensional velocities).The model can also accommodate various non-Gaussian wind fields and a wide range of skewness–kurtosis combinations.Moreover,improved skewness and kurtosis in the simulated velocity will result in a significantly different dispersion for wind/particle simulations.Thus,the non-Gaussian model is worth applying to wind field simulation in the surface layer.

ALMOST SURELY TIME-SPACE INTERMITTENCY FOR THE PARABOLIC ANDERSON MODEL WITH A LOG-CORRELATED GAUSSIAN FIELD

In this paper, we consider the continuous parabolic Anderson model with a logcorrelated Gaussian field, and obtain the precise quenched long-time asymptotics and spatial asymptotics. To overcome the difficulties arising from the log-correlated Gaussian field in the proof of the lower bound of the spatial asymptotics, we first establish the relation between quenched long-time asymptotics and spatial asymptotics, and then get the lower bound of the spatial asymptotics through the lower bound of the quenched long-time asymptotics.

A Physiologically-Based Adaptive Three-Gaussian Function Model for Image Enhancement

Image enhancement is an important pre-processing step for various image processing applications. In this paper, we proposed a physiologically-based adaptive three-Gaussian model for image enhancement. Comparing to the standard three-Gaussian model inspired by the spatial structure of the receptive field (RF) of the retinal ganglion cells, the proposed model can dynamically adjust its parameters according to the local image luminance and contrast based on the physiological findings. Experimental results on several images show that the proposed adaptive three-Gaussian model achieves better performance than the classical method of histogram equalization and the standard three-Gaussian model.

Calculation of watershed flow concentration based on the grid drop concept

The grid drop concept is introduced and used to develop a micromechanism-based methodology for calculating watershed flow concentration. The flow path and distance traveled by a grid drop to the outlet of the watershed are obtained using a digital elevation model （DEM）. Regarding the slope as an uneven carpet through which the grid drop passes, a formula for overland flow velocity differing from Manning＇s formula for stream flow as welt as Darcy＇s formula for pore flow is proposed. Compared with the commonly used unit hydrograph and isochronal methods, this new methodology has outstanding advantages in that it considers the influences of the slope velocity field and the heterogeneity of spatial distribution of rainfall on the flow concentration process, and includes only one parameter that needs to be calibrated. This method can also be effectively applied to the prediction of hydrologic processes in un-gauged basins.

Acoustic radiation force on a multilayered sphere in a Gaussian standing field

We develop a model for calculating the radiation force on spherically symmetric multilayered particles based on the acoustic scattering approach.An expression is derived for the radiation force on a multilayered sphere centered on the axis of a Gaussian standing wave propagating in an ideal fluid,The effects of the sound absorption of the materials and sound wave on acoustic radiation force of a multilayered sphere immersed in water are analyzed,with particular emphasis on the shell thickness of every layer,and the width of the Gaussian beam.The results reveal that the existence of particle trapping behavior depends on the choice of the non-dimensional frequency ka,as well as the shell thickness of each layer.This study provides a theoretical basis for the development of acoustical tweezers in a Gaussian standing wave,which may benefit the improvement and development of acoustic control technology,such as trapping,sorting,and assembling a cell,and drug delivery applications.

On-line estimation of concentration parameters in fermentation processes

It has long been thought that bioprocess, with their inherent measurement difficulties and complex dynamics, posed almost insurmountable problems to engineers. A novel software sensor is proposed to make more effective use of those meas- urements that are already available, which enable improvement in fermentation process control. The proposed method is based on mixtures of Gaussian processes (GP) with expectation maximization (EM) algorithm employed for parameter estimation of mixture of models. The mixture model can alleviate computational complexity of GP and also accord with changes of operating condition in fermentation processes, i.e., it would certainly be able to examine what types of process-knowledge would be most relevant for local models’ specific operating points of the process and then combine them into a global one. Demonstrated by on-line estimate of yeast concentration in fermentation industry as an example, it is shown that soft sensor based state estimation is a powerful technique for both enhancing automatic control performance of biological systems and implementing on-line moni- toring and optimization.

Probabilistic Model for Wind Speed Variability Encountered by a Vessel

As a result of social awareness of air emission due to the use of fossil fuels, the utilization of the natural wind power resources becomes an important option to avoid the dependence on fossil resources in industrial activities. For example, the maritime industry, which is responsible for more than 90% of the world trade transport, has already started to look for solutions to use wind power as auxiliary propulsion for ships. The practical installation of the wind facilities often requires large amount of investment, while uncertainties for the corresponding energy gains are large. Therefore a reliable model to describe the variability of wind speeds is needed to estimate the expected available wind power, coefficient of the variation of the power and other statistics of interest, e.g. expected length of the wind conditions favorable for the wind-energy harvesting. In this paper, wind speeds are modeled by means of a spatio-temporal transformed Gaussian field. Its dependence structure is localized by introduction of time and space dependent parameters in the field. The model has the advantage of having a relatively small number of parameters. These parameters have natural physical interpretation and are statistically fitted to represent variability of observed wind speeds in ERA Interim reanalysis data set.

Two-Dimensional Lithium-Ion Battery Modeling with Electrolyte and Cathode Extensions

A two-dimensional model for transport and the coupled electric field is applied to simulate a charging lithium-ion cell and investigate the effects of lithium concentration gradients within electrodes on cell performance. The lithium concentration gradients within electrodes are affected by the cell geometry. Two different geometries are investigated: extending the length of the electrolyte past the edges of the electrodes and extending the length of the cathode past the edge of the anode. It is found that the electrolyte extension has little impact on the behavior of the electrodes, although it does increase the effective conductivity of the electrolyte in the edge region. However, the extension of the cathode past the edge of the anode, and the possibility for electrochemical reactions on the flooded electrode edges, are both found to impact the concentration gradients of lithium in electrodes and the current distribution within the electrolyte during charging. It is found that concentration gradients of lithium within electrodes may have stronger impacts on electrolytic current distributions, depending on the level of completeness of cell charge. This is because very different gradients of electric potential are expected from similar electrode gradients of lithium concentrations at different levels of cell charge, especially for the LixC6 cathode investigated in this study. This leads to the prediction of significant electric potential gradients along the electrolyte length during early cell charging, and a reduced risk of lithium deposition on the cathode edge during later cell charging, as seen experimentally by others.

An improved potential field method for mobile robot navigation

In order to overcome the inherent oscillation problem of potential field methods(PFMs) for autonomous mobile robots in the presence of obstacles and in narrow passages,an enhanced potential field method that integrates Levenberg-Marquardt(L-M) algorithm and k-trajectory algorithm into the basic PFMs is proposed and simulated.At first,the mobile robot navigation function based on the basic PFMs is established by choosing Gaussian model.Then,the oscillation problem of the navigation function is investigated when a mobile robot nears obstacles and passes through a long and narrow passage,which can cause large computation cost and system instability.At last,the L-M algorithm is adopted to modify the search direction of the navigation function for alleviating the oscillation,while the k-trajectory algorithm is applied to further smooth trajectories.By a series of comparative experiments,the use of the L-M algorithm and k-trajectory algorithm can greatly improve the system performance with the advantages of reducing task completion time and achieving smooth trajectories.

外场中一种钻石型等级晶格上Gaussian模型的临界性质

利用重正化群变换方法，在一种特殊钻石型等级晶格上研究了有外场存在时Gaussian模型的临界性质。结果表明：与一般的钻石型等级晶格上的结果相比，在临界点上，格点近邻相互作用参量和外磁场都具有相同的形式，但临界指数不相同，这表明这两种晶格的铁磁性质属于不同的普适类。

Modeling of the nonlinear acoustic field generated from a phased array using Gaussian superposition technique

The nonlinearity has significant effect on the ultrasonic therapy using phased ar- rays. A numerical approach is developed to calculate the nonlinear sound field generated from a phased array based on the Gaussian superposition technique. The parameters of the phased array elements are first estimated from the focal parameters using the inverse matrix algorithm; Then the elements are expressed as a set of Gaussian functions; Finally, the nonlinear sound field can be calculated using the Gaussian superposition technique. In the numerical simulation, a 64~ 1 phased array is used as the transmitter. In the linear case, the difference between the results of the Gaussian superposition technique and the Fresnel integral is less than 0.5%, which verifies the feasibility of the approach. In the nonlinear case, the nonlinear fields of single-focus modes and double-focus modes are calculated. The results reveal that the nonlinear effects can improve the focusing performance, and the nonlinear effects are related with the source pressures and the excitation frequencies.

Segmentation of MS lesions using entropy-based EM algorithm and Markov random fields

This paper presents an approach for fully automatic segmentation of MS lesions in fluid attenuated inversion recovery (FLAIR) Magnetic Resonance (MR) images. The proposed method estimates a gaussian mixture model with three kernels as cerebrospinal fluid (CSF), normal tissue and Multiple Sclerosis lesions. To estimate this model, an automatic Entropy based EM algorithm is used to find the best estimated Model. Then, Markov random field (MRF) model and EM algorithm are utilized to obtain and upgrade the class conditional probability density function and the apriori probability of each class. After estimation of Model parameters and apriori probability, brain tissues are classified using bayesian classification. To evaluate the result of the proposed method, similarity criteria of different slices related to 20 MS patients are calculated and compared with other methods which include manual segmentation. Also, volume of segmented lesions are computed and compared with gold standard using correlation coefficient. The proposed method has better performance in comparison with previous works which are reported here.

基于FPGA的两阶段配电网拓扑实时辨识算法

对配电网拓扑进行准确的实时辨识是电力系统安全稳定运行的基础,但随着新能源的接入以及配电网规模不断增大,配电网拓扑结构的动态变化愈加频繁且难以辨识。然而,现有配电网拓扑辨识算法所使用的历史数据需要人工对其进行拓扑标注,且拓扑辨识时间长,难以实现配电网拓扑实时辨识。因此,文中提出了一种基于现场可编程逻辑门阵列(FPAG)的两阶段配电网拓扑结构实时辨识算法。该算法不需要预先给出配电网拓扑类别的数量,即可对已有历史数据进行相应的拓扑标注及分类,并且基于FPGA实现了对配电网拓扑的实时辨别。该算法分为2个阶段:第1阶段采用变分贝叶斯高斯混合模型,对已有历史数据进行相应的拓扑标注及分类;第2阶段采用麻雀搜索算法,使得支持向量机快速收敛得到最优参数,以实现对配电网拓扑结构的精准辨识。基于该算法,利用FPGA并行架构以及高速高密度特性建立了实时拓扑结构辨识平台。最后,通过算例分析验证了所提辨识方法的有效性和优越性。

基于能量场的城市道路车辆交互强度研究

由于交通环境的复杂性、车辆之间的交互多变性,无人驾驶的行为决策研究一直存在应用灵活性较差、精度不高的瓶颈。因此,以探究车辆之间的交互机理为目标,深入研究车流运行的微观规律,为无人驾驶的行为决策研究提供理论依据。首先,基于能量场的物理性质,将车辆类比于引力场中的场源,建立车辆的行车交互场模型,并依据能量场中的质量和车辆物理特性定义了交互虚拟质量,例如速度、加速度、车型。采用行车交互力模型量化车辆之间的交互程度,依据临界车头间距与多普勒效应分别重新定义交通环境中的距离和速度。其次,利用实车在上海浦东新区同顺大道采集速度、相对距离等相关数据,通过视频处理软件Kinovea提取行车记录仪中的数据,采用高斯混合模型验证行车交互力与实际驾驶行为之间的关系。最后,通过K-means算法对行车交互力聚类分析,量化车辆行驶风险等级。结果表明:通过高斯混合模型计算出的跟驰、换道分类结果与实际分类结果的误差分别为1.12%和9.1%,说明行车交互力对车辆交互的量化描述能力较好;同时,在行车交互力模型的基础上将行车风险分为4级,有效评估了行车风险。本研究提出的行车交互力模型不仅可以拓展以往行车安全场的应用范围,也为驾驶行为决策研究提供一定的理论支撑。

基于深度学习方法的传送带缺陷检测

针对传送带瑕疵在图像中所占有的像素相对有限、特征相对微弱且分布不均匀的问题,设计了一个传送带缺陷检测系统,并提出了一种基于高斯混合模型的标签分配策略;利用特征感受野遵循高斯分布的先验信息进行高斯建模,并通过动态调整机制适应不同尺度的传送带缺陷,能够更有效地提升对微小瑕疵的捕捉能力;使用感受野距离取代交并比来衡量高斯感受野和真实标签的相似度,并通过二者之间的相似度来分配样本,从而有效提高了样本分配的准确性;使用高斯混合模型并通过期望最大化算法拟合概率分布,实现了对特征点的自适应正负样本分配,能够有效避免微小瑕疵特征微弱所导致的漏检问题;结果表明,高斯混合模型标签分配策略对传送带缺陷检测精度的提升十分明显,相对于基准网络,精度提升3.8%。

电碳材料燃烧排放对大气颗粒物浓度的影响研究

电碳材料燃烧排放产生的颗粒物在大气中传输和扩散受到风场和大气条件的影响,其中包括风速、温度和湿度的变化和不确定性,预测电碳材料燃烧排放的分布变得困难。因此,研究电碳材料燃烧排放对大气颗粒物浓度的影响。使用大气监测仪器收集数据,并建立高斯烟羽模型,模拟电碳材料燃烧排放颗粒物在大气中的沉积与扩散情况。将辽宁省某火电厂作为监测区域,采用线性回归分析方法分析并验证了电碳燃烧排放颗粒物浓度与气象因子之间的关系。通过不同方法对比说明:所提方法分析出的电碳材料燃烧排放对大气颗粒物浓度的影响更符合实际情况。

综掘工作面呼吸性粉尘浓度时空场函数研究

综掘工作面呼吸性粉尘浓度时空场函数研究是粉尘防治和尘肺预警的基础。分析了综掘工作面呼吸性粉尘浓度监测关键点,提出呼吸性粉尘浓度传感器测点布置方案;以关键监测点的呼吸性粉尘浓度传感器实测数据作为实时来源,对比剖析了距离加权反比法和克里金法的优缺点,建立了一种扩展的空间插值算法;归纳半变异理论,将呼吸性粉尘浓度变化的时间维度和空间维度引入到半变异函数中,得到一种呼吸性粉尘时空场算法,建立综掘工作面呼吸性粉尘浓度时空场函数模型;最后,以河南新桥煤矿2502工作面作为对象,以滤膜称重法为标准,对时空场函数进行了试验验证。结果发现:在综掘工作面司机5~10 m、端头回风侧10~15 m区域内的呼吸性粉尘浓度较高且变化较剧烈,而在回风侧15 m后方呼吸性粉尘浓度开始逐步趋于平稳降低;综掘工作面呼吸性粉尘浓度时空场函数模型计算结果相对误差为±14.8%,比克里金法小±10.8%,比距离加权反比法小±22.4%。研究结果表明,综掘工作面呼吸性粉尘浓度时空场函数模型将时间维度和空间维度纳入了权重系数中,构建的时空场函数模型能更好地提高插值计算的精度,提升去特异值点的能力。