考虑黏土土性参数与支护压力变异性的盾构掌子面稳定性分析

盾构掌子面稳定性的不确定性分析多侧重于土性参数的变异性,较少考虑支护压力的变异性。基于K-L级数分解法建立描述土性参数空间变异性的三维随机场,研究土性参数变异性对掌子面失稳模式、极限支护应力的影响规律,讨论支护压力的均值与变异系数对失效概率的影响,并据此确定支护压力均值特征值。结果表明：黏性土黏聚力与内摩擦角的空间变异性对掌子面稳定性有重要影响,其中内摩擦角的影响更甚;掌子面失稳模式与随机场局部分布密切相关,当掌子面前方随机场较分散时,可能发生局部破坏;掌子面的失效概率与支护压力的均值和变异系数密切相关,支护压力的均值越大,变异系数越小,失效概率越小;提出了掌子面支护压力均值特征值的概念,并结合失效概率给出了确定方法。     

50年来辽宁省不同等级舒适日数演变及空间区划分析

根据1964—2015年辽宁省23个气象站点的逐日平均气温、相对湿度及平均风速资料,采用人体舒适度指数法计算人体舒适度指数,在季尺度上分析辽宁省不同等级舒适日数演变情况及典型旅游城市最佳旅游期;运用旋转经验正交函数分解法(REOF),分析人体舒适度指数季尺度空间变化特征,并应用ArcGIS软件进行舒适区域划分。结果表明:①辽宁省多年平均冷不舒适日数呈降低趋势,舒适日数呈增加趋势,热不舒适日数也呈微弱增加趋势;舒适程度夏季＞秋季＞春季＞冬季;②除冬季外5座典型旅游城市均适宜旅游,夏季为最佳旅游期;其中,沈阳、本溪更适宜春季旅游,大连更适宜秋季旅游。③辽宁省四季舒适度变化情况可大致划分为辽西、辽中、辽东三个区域,具体划分情况随季节有相应变化,总体舒适度由辽宁东部向西部逐渐递减。     

Peer-to-peer bichromatic reverse nearest neighbours in mobile ad-hoc networks

The increasing use of mobile communications has raised many issues of decision support and resource allocation. A crucial problem is how to solve queries of Reverse Nearest Neighbour (RNN). An RNN query returns all objects that consider the query object as their nearest neighbour. Existing methods mostly rely on a centralised base station. However, mobile P2P systems offer many benefits, including self-organisation, fault-tolerance and load-balancing. In this study, we propose and evaluate 3 distinct P2P algorithms focusing on bichromatic RNN queries, in which mobile query peers and static objects of interest are of two different categories, based on a time-out mechanism and a boundary polygon around the mobile query peers. The Brute-Force Search Algorithm provides a naive approach to exploit shared information among peers whereas two other Boundary Search Algorithms filter a number of peers involved in query processing. The algorithms are evaluated in the MiXiM simulation framework with both real and synthetic datasets. The results show the practical feasibility of the P2P approach for solving bichromatic RNN queries for mobile networks.     

Computational Problem Solving in Spatial Substrates -- A Cognitive Systems Engineering Approach

The ability to perform spatial tasks is crucial for everyday life and of great importance to cognitive agents such as humans, animals, and autonomous robots. A common artificial intelligence approach to accomplish spatial tasks is to represent spatial configurations and tasks in form of detailed knowledge about various aspects of space and time. Suitable algorithms then use the representations to compute solutions to spatial problems. In comparison, natural embodied and situated agents often solve spatial tasks without detailed knowledge about geometric, topological, or mechanical laws; they directly relate actions to effects that are due to spatio-temporal affordances in their bodies and environments. Accordingly, we propose a paradigm that makes the spatio-temporal substrate an integral part of the engine that drives spatial problem solving. We argue that spatial and temporal structures in body and environment can substantially support (and even replace) reasoning effort in computational processes: physical manipulation and perception in spatial environments substitute formal computation. While the approach is well known – for example, we employ diagrams as spatial substrate for geometric problem solving and maps for wayfinding – the underlying principle has not been systematically investigated or formally analyzed as a paradigm of cognitive processing. Topology, distance, and orientation constraints are all integrated and interdependent in truly 2- or 3-dimensional space. Exploiting this fact may not only help overcome the need for acquiring detailed knowledge about the interrelationships between different aspects of space; it also can point to a way of avoiding exploding computational complexity that occurs when we deal with these aspects of space in complex real-world scenarios. Our approach employs affordance-based object-level problem solving to complement knowledge-level formal approaches. We will assess strengths and weaknesses of the new cognitive systems paradigm.     

Spatial and Temporal Distinction of Microelemental Signatures of Missouri River Tributaries

The microchemical composition of a fish's calcified structure, such as an otolith, fin ray, or scale, is a ‘biological tag’ that reflects the use of different habitats throughout its life history. Hard‐part microchemistry has the potential to address many fish conservation, management, and behavior questions. In order to use hard‐part microchemistry to address fisheries research questions, elemental signatures of water must be distinct at the spatial scale of interest and ideally temporally stable. The goal of this study was to assess whether spatial differences existed in the concentrations of five elements [barium (¹³⁷Ba), magnesium (²⁴Mg), manganese (⁵⁵Mn), sodium (²³Na), and strontium (⁸⁸Sr)] between and within eight Missouri River tributaries and whether those signatures were temporally stable. All elemental concentrations were converted to molar ratios (mmol mol^?1) using calcium (⁴³Ca) concentrations as the base. Canonical correspondence analysis showed distinct differences in Mg:Ca, Na:Ca, and Sr:Ca concentrations between the eight tributaries. Cochran–Mantel–Haenszel tests showed that sites within a tributary were distinguished using Mg:Ca and Na:Ca concentrations. However, only Mg:Ca concentrations were temporally stable. Results from this study demonstrate the potential for using hard‐part microchemistry to address various questions at multiple spatial scales in the Missouri River riverscape but also highlight the importance of evaluating water microelemental signatures prior or simultaneous to any hard‐part microchemistry study. Copyright © 2016 John Wiley & Sons, Ltd.     

基于经纬网格的递增KNN位置隐私保护查询算法

为了在使用基于位置的服务时用户的位置信息不被不可信的位置服务提供商所泄漏,k-匿名位置隐私保护已被广泛研究.然而在集中匿名器被黑客控制时原k-匿名算法会泄漏所有用户的位置隐私,在进行k个最近邻目标查询时对网络的负载较重,而SpaceTwist算法又不能保证k-匿名.提出了一种基于经纬网格的递增KNN位置隐私保护查询算法,将经典的k-匿名算法与SpaceTwist算法相杂交,并引入经纬网格代替原来精确的位置上报给集中匿名器,从而解决了上述问题.实验证明基于经纬网格的递增KNN查询算法比较节省从集中匿名器到位置服务提供商的服务器之间的网络流量.     

脑电Laplacian空域滤波的改进算法

Laplacian空域滤波通过被关注的通道与相邻通道信号转换,能有效地提高脑电信号的信噪比,经典的Laplacian空域滤波矩阵由通道之间的距离确定.该方法依赖于相应通道定位的准确性,实际应用中不能保证电极精准安放并存在个体差异,影响了该方法的应用效果.为了提高该算法的通用性,采用高斯模型改进经典Laplacian空域滤波算法,根据用户调试数据确定模型相关参数,进而确定空域滤波矩阵.采用国际脑机接口竞赛BCI competition 2005 Ⅳ数据集验证滤波后的效果,总体比经典Laplacian方法识别准确度提高10个百分比,采用改进方法滤波后不同类间距离增大、同类间距离减小,提高了信号的信噪比.     

基于随机词汇迭代模型的POI分类检索

从特征选择、局部区域划分和词汇语义相似性计算入手,利用随机词汇迭代模型(random terms iterativemodel,RTIM)进行海量兴趣点(point of interest,POI)文本分类.通过词汇频度、集中度和离散度方法筛选出特征词汇;依据文本与各POI类别间的相似度进行局部区域划分;在每个局部区域内基于词汇在文本中的排列顺序构建词频向量,基于词频向量中词频的随机删除和重构,获取特征映射矩阵;通过特征映射矩阵将文本转为特征向量,并采用SVM分类器进行POI文本分类.实验证明,该方法有效提升了POI文本分类准确性和覆盖率.     

基于各向异性滤波和空间FCM的MRI图像分割方法

针对具复杂目标和边界模糊的MRI图像中多感兴趣区域的分割中分割MRI图像软组织难的问题, 提出了一种基于各向异性滤波和空间模糊C-均值聚类(SFCM)的MRI图像分割方法; 用新型各向异性滤波对图像进行预处理, 解决去噪平滑的同时弱化图像细节的问题; 用邻域空间信息设计空间函数, 改进传统FCM的目标函数; 用图像的空间信息实现图像各目标准确分类、有效解决孤立区域的正确归类问题, 进而使分割区域完整; 用直方图拟合曲线初始化分类数和初始聚类中心, 加快算法迭代到最优解, 进而减少运行时间。通过实验证实了各向异性滤波和空间FCM的MRI图像分割方法的综合应用显著提高了分割灰度重叠、目标不连续和目标边界模糊的MRI图像的分割效果。     

空间资源索引与top-k查询研究

以空间资源索引结构R-tree为基础, 考虑人们对空间资源能力指标的要求, 利用道路网络模型进行空间距离的计算, 提出了一种包含能力维度信息的空间资源索引结构和top-k查询算法, 并与传统遍历算法进行对比实验, 验证了查询算法的有效性。