Automatic brain tissue segmentation in MR images using hybrid atlas forest based on confidence-weighted probability matrix

The segmentation of specific tissues in an MR brain image for quantitative analysis can assist the disease diagnosis and medical research. Therefore, a robust and accurate method for automatic segmentation is necessary. Atlas-based-method is a common and effective method of automatic segmentation where an atlas refers to a pair of image consist of an intensity image and its corresponding label image. Apart from the general multi-atlas-based methods, which propagate labels through the single atlas then fuse them, we proposed a hybrid atlas forest based on confidence-weighted probability matrix to consider the atlases set as a whole and treat each voxel differently. In the framework, we first register the atlas to the image space of target and calculate the confidence of voxels in the registered atlas. Then, a confidence-weighted probability matrix is generated and it augments to the intensity image of the atlas or target for providing spatial information of the target tissue. Third, a hybrid atlas forest is trained to gather the features and correlation information among the atlases in the dataset. Finally, the segmentation of the target tissues is predicted by the trained hybrid atlas forest. The segment performance and the components efficiency of the proposed method are evaluated on the two public datasets. Based on the experiment results and quantitative comparisons, our method can gather spatial information and correlation among the atlases to obtain an accurate segmentation.     

Advances in statistical mechanics of rock masses and its engineering applications

To efficiently link the continuum mechanics for rocks with the structural statistics of rock masses,a theoretical and methodological system called the statistical mechanics of rock masses(SMRM)was developed in the past three decades.In SMRM,equivalent continuum models of stressestrain relationship,strength and failure probability for jointed rock masses were established,which were based on the geometric probability models characterising the rock mass structure.This follows the statistical physics,the continuum mechanics,the fracture mechanics and the weakest link hypothesis.A general constitutive model and complete stressestrain models under compressive and shear conditions were also developed as the derivatives of the SMRM theory.An SMRM calculation system was then developed to provide fast and precise solutions for parameter estimations of rock masses,such as full-direction rock quality designation(RQD),elastic modulus,Coulomb compressive strength,rock mass quality rating,and Poisson’s ratio and shear strength.The constitutive equations involved in SMRM were integrated into a FLAC3D based numerical module to apply for engineering rock masses.It is also capable of analysing the complete deformation of rock masses and active reinforcement of engineering rock masses.Examples of engineering applications of SMRM were presented,including a rock mass at QBT hydropower station in northwestern China,a dam slope of Zongo II hydropower station in D.R.Congo,an open-pit mine in Dexing,China,an underground powerhouse of Jinping I hydropower station in southwestern China,and a typical circular tunnel in Lanzhou-Chongqing railway,China.These applications verified the reliability of the SMRM and demonstrated its applicability to broad engineering issues associated with jointed rock masses.     

Design and calibration of a laminar soil box suitable for a low-capacity shake table using free-field tests on Ganga sand

The present study concentrates on design, commissioning and calibration of a uniaxial laminar soil box suitable for use on a low base-shear capacity shake table available at IIT Kanpur, India. The box is designed to simulate the behavior of soil deposits subjected to earthquake motions, with minimal boundary effects due to reflection of waves at the boundary. The 1.1 m × 1.6 m × 0.765 m box is comprised of a series of individual lamina supported independently on multiple roller bearings guided through a guide channel. The outer frame connected to the guide rods is designed in such as way that it can transfer the self weight of each lamina out of the shake table. A series of free-field tests are carried out on dry Ganga sand sample to calibrate the box. Dynamic response parameters, such as acceleration, displacement, stress-strain behavior, strain-dependant modulus and damping ratio of the sand at various depth are investigated. Large strain and subsequent increased inelasticity is observed towards the top of the sand bed. The experimental results are further compared with equivalent-linear SHAKE analysis and nonlinear finite element ground response analysis of the free-field soil using OpenSees for assessing the performance of the laminar box.     

基于NB分类器重访概率预测的Web缓存替换策略

Web缓存是用来解决网络访问延迟和网络拥塞问题，缓存替换策略直接影响缓存的命中率。为此，提出一种朴素贝叶斯（NB）分类器重访概率预测的Web缓存替换策略；根据用户之前访问日志，通过分区操作提取多项特征来表示每次访问的对象，并构建特征数据集；训练NB分类器，用来确定缓存中对象被再次访问的概率，为对象分配权重；结合LRU策略来合理删除一些对象。仿真结果表明，提出的策略在保证较高命中率的同时有效降低了执行时间。     

长江武惠堤堤防渗透破坏风险计算模型及应用

针对渗透水压力引起堤防渗透破坏问题,以堤防渗透破坏风险为目标,考虑堤防计算水位条件和土层渗透系数的不确定性,建立了堤防渗透破坏风险计算模型。以长江武惠堤17+750断面为例,对汉口水文站水位监测资料进行分析并拟合水位概率密度函数,对该断面渗流规律进行有限元分析,从而拟合渗透破坏概率密度函数,以此建立该断面堤防渗透破坏风险定量表达式。研究结果表明,武惠堤17+750断面堤防在警戒水位与防洪设计水位下,渗透破坏概率分别为0.442 9、0.764 0,渗透破坏风险分别为0.001 421、0.002 52;堤防渗透破坏风险随着堤外水位的升高而增加,但在防洪设计水位内运行时,堤防渗透破坏风险低,堤防渗流安全可得到有效控制。     

Throughput-based fair bandwidth allocation in OBS networks

Fair bandwidth allocation (FBA) has been studied in optical burst switching (OBS) networks, with the main idea being to map the max-min fairness in traditional IP networks to the fair-loss probability in OBS networks. This approach has proven to be fair in terms of the bandwidth allocation for differential connections, but the use of the ErlangB formula to calculate the theoretical loss probability has made this approach applicable only to Poisson flows. Furthermore, it is necessary to have a reasonable fairness measure to evaluate FBA models. This article proposes an approach involving throughput-based-FBA, called TFBA, and recommends a new fairness measure that is based on the ratio of the actual throughput to the allocated bandwidth. An analytical model for the performance of the output link with TFBA is also proposed.     

铸造式和焊接式主轴箱体的动态特性对比分析

利用有限元法和试验模态法对立式加工中心的铸造式和焊接式两种结构的主轴箱体进行了模态分析,分别获得了其前六阶固有频率和振型。通过对比两种方法获得的结果,验证了有限元分析模型的有效性。研究表明,两种主轴箱体的阻尼比接近,但焊接式主轴箱体的各阶固有频率均要高于铸造式主轴箱体的各阶固有频率。并且铸造式主轴箱体的固有频率更接近于机床主轴的常用工作频率,焊接式主轴箱体的则远离此频率。因此对于常用主轴转速而言,焊接式主轴箱体的动态性能要优于铸造式主轴箱体的动态性能。     

变分布的量子行为粒子群优化算法求解工程约束优化问题

针对工程形状设计领域中带有多个约束条件的非线性设计优化问题,提出了一种自适应的基于高斯分布的量子行为粒子群优化(AG-QPSO)算法。通过自适应地调整高斯分布,AG-QPSO算法能够在搜索的初始阶段有很强的全局搜索能力,随着搜索过程的进行,算法的局部搜索能力逐渐增强,从而满足了算法在搜索过程不同阶段的需要。为了验证算法的有效性,在压力容器和张弦设计问题这两个工程约束优化问题上进行50轮独立实验。实验结果表明,在满足所有约束条件的情况下,AG-QPSO算法在压力容器设计问题上取得了5890.9315的平均解和5885.3328的最优解,在张弦设计问题上取得了0.01096的平均解和0.01096的最优解,远优于标准粒子群优化(PSO)算法、具有量子行为的粒子群优化(QPSO)算法和高斯量子行为粒子群(G-QPSO)算法等现有的算法的结果,同时AG-QPSO算法取得的结果的方差较小,说明该算法具有很好的鲁棒性。     

A hybrid evaluation method for human error probability by using extended DEMATEL with Z-numbers: A case of cargo loading operation

Human error probability (HEP) evaluation and prediction is one of the most significant tasks to enhance human reliability in marine industry. Among various kinds of HEP evaluation techniques, the Human Error Assessment and Reduction Technique (HEART) technique is regarded as an effective and empirical tool that has been widely adopted in various fields. However, current HEART techniques are insufficient to address HEP evaluation problem in which the self-assurance of expert's judgment and inter-dependencies between Error-producing conditions (EPCs) are considered. Therefore, the purpose of this paper is to develop a hybrid HEART framework (H-HEART-F) to address this problem by integrating Z-numbers and the decision-making trial and evaluation laboratory (DEMATEL) method. First, the Z-numbers are introduced to model the uncertainty and self-assurance of evaluation information from various experts. Then, the Z-number power weighted average (Z-PWA) operator is proposed to aggregate the individual evaluation information into a group direct influenced matrix. Next, an extended DEMATEL method based on possibility degree measure is constructed to determine the proportion of effect of each EPC by considering the self-assurance of expert's judgment and inter-dependencies between EPCs. Finally, the HEP estimation for the cargo loading operation in oil or chemical tanker ship is presented to demonstrate the availability and feasibility of the H-HEART-F. After that, the sensitivity analysis and comparison study are conducted to further illustrate the reasonableness and effectiveness of the proposed method.     

Efficient estimation of extreme quantiles using adaptive kriging and importance sampling

This study considers an efficient method for the estimation of quantiles associated to very small levels of probability (up to O(10⁻⁹)), where the scalar performance function J is complex (eg, output of an expensive-to-run finite element model), under a probability measure that can be recast as a multivariate standard Gaussian law using an isoprobabilistic transformation. A surrogate-based approach (Gaussian Processes) combined with adaptive experimental designs allows to iteratively increase the accuracy of the surrogate while keeping the overall number of J evaluations low. Direct use of Monte-Carlo simulation even on the surrogate model being too expensive, the key idea consists in using an importance sampling method based on an isotropic-centered Gaussian with large standard deviation permitting a cheap estimation of small quantiles based on the surrogate model. Similar to AK-MCS as presented in the work of Schöbi et al., (2016), the surrogate is adaptively refined using a parallel infill criterion of an algorithm suitable for very small failure probability estimation. Additionally, a multi-quantile selection approach is developed, allowing to further exploit high-performance computing architectures. We illustrate the performances of the proposed method on several two to eight-dimensional cases. Accurate results are obtained with less than 100 evaluations of J on the considered benchmark cases.