Probabilistic learning on manifolds (PLoM) with partition

The probabilistic learning on manifolds (PLoM) introduced in 2016 has solved difficult supervised problems for the “small data” limit where the number N of points in the training set is small. Many extensions have since been proposed, making it possible to deal with increasingly complex cases. However, the performance limit has been observed and explained for applications for which N is very small and for which the dimension of the diffusion-map basis is close to N. For these cases, we propose a novel extension based on the introduction of a partition in independent random vectors. We take advantage of this development to present improvements of the PLoM such as a simplified algorithm for constructing the diffusion-map basis and a new mathematical result for quantifying the concentration of the probability measure in terms of a probability upper bound. The analysis of the efficiency of this extension is presented through two applications.     

Various density light field image coding based on distortion minimization interpolation

In recent years, the light field (LF) as a new imaging modality has attracted wide interest. The large data volume of LF images poses great challenge to LF image coding, and the LF images captured by different devices show significant differences in angular domain. In this paper we propose a view prediction framework to handle LF image coding with various sampling density. All LF images are represented as view arrays. We first partition the views into reference view (RV) set and intermediate view (IV) set. The RVs are rearranged into a pseudo sequence and directly compressed by a video encoder. Other views are then predicted by the RVs. To exploit the four dimensional signal structure, we propose the linear approximation prior (LAP) to reveal the correlation among LF views and efficiently remove the LF data redundancy. Based on the LAP, a distortion minimization interpolation (DMI) method is used to predict IVs. To robustly handle the LF images with different sampling density, we propose an Iteratively Updating depth image based rendering (IU-DIBR) method to extend our DMI. Some auxiliary views are generated to cover the target region and then the DMI calculates reconstruction coefficients for the IVs. Different view partition patterns are also explored. Extensive experiments on different types LF images also valid the efficiency of the proposed method.     

瞬变电磁井间勘探的全空间几何因子

井间是剩余油的主要分布区域,为探测井间剩余油,提高采收率,提出了基于全空间几何因子的瞬变电磁井间勘探方法。在本井使用线圈发射、邻井使用线圈接收,根据瞬变电磁场理论,在阶跃信号的激励下发射线圈在地层中激发出沿圆周方向的闭合瞬变电场,该电场在导电地层中产生与地层电导率呈正比的涡流。由Doll地层环模型可知,地层中的涡流在空间任意点激发得到与地层电导率成正比的二次场响应信号(有用信号),并可表示为空间各点电导率的加权平均值,其权重即为井间瞬变电磁勘探的全空间几何因子;全空间几何因子集中分布在发射线圈和接收线圈附近,其它区域分布较少,在发射线圈和接收线圈两侧呈现不同的极性;对瞬变电磁响应与地层电导率、井间距和源距的变化规律研究可知,瞬变电磁井间勘探有用信号随着地层电导率的增大而增大,随着井间距的增加单调减小,在发射线圈和接收线圈处于同一深度时该响应信号幅度最大。     

Adaptive Discretization for Computerized Tomography

Two adaptive discretization frameworks are tested for computerized tomography (CT) data reconstruction. Removal of inactive pixels is primary motivation. Efficient and user independent entropy optimized masking is employed for spatial filtering purposes. Density of nodes at high gradient of reconstructed physical property is used as adaptation criterion. An alternative option, independent from noisy projection data and nature of the physical properties, is also discussed. Sensitivity analysis between the uniform and nonuniform (evolved via adaptive route) reconstruction grid reveals the utility of nonuniform grids. Iterative and transform based reconstruction techniques are used. Outcomes are tested successfully on three real world projection data from two different compact CT setups and one commercial high-resolution micro-CT scanner.     

Perception‐aware autonomous mast motion planning for planetary exploration rovers

Highly accurate real‐time localization is of fundamental importance for the safety and efficiency of planetary rovers exploring the surface of Mars. Mars rover operations rely on vision‐based systems to avoid hazards as well as plan safe routes. However, vision‐based systems operate on the assumption that sufficient visual texture is visible in the scene. This poses a challenge for vision‐based navigation on Mars where regions lacking visual texture are prevalent. To overcome this, we make use of the ability of the rover to actively steer the visual sensor to improve fault tolerance and maximize the perception performance. This paper answers the question of where and when to look by presenting a method for predicting the sensor trajectory that maximizes the localization performance of the rover. This is accomplished by an online assessment of possible trajectories using synthetic, future camera views created from previous observations of the scene. The proposed trajectories are quantified and chosen based on the expected localization performance. In this study, we validate the proposed method in field experiments at the Jet Propulsion Laboratory (JPL) Mars Yard. Furthermore, multiple performance metrics are identified and evaluated for reducing the overall runtime of the algorithm. We show how actively steering the perception system increases the localization accuracy compared with traditional fixed‐sensor configurations.     

基于多元神经网络融合的分布式资源空间文本分类研究

针对实体产业对科技资源的服务需求,以服务效应作为资源文本分类标准,提出一种基于多元神经网络融合的分布式资源空间文本分类模型。设计了包含词嵌入层、卷积层、双向门控循环单元层、注意力机制层和softmax层的多元神经网络通路;在此基础上采用基于需求—效应—资源分类策略,完成了从定性科技资源需求到定量资源服务效应求解,再到定性科技资源输出的映射变换,重点解决了分布式科技资源局部和全局语义特征形式多样、文本长距离依赖特征显著、重要资源信息难以准确识别的问题,进而从分布式科技资源空间中快速准确地获取效应知识,提升实体产业产品研发效率和创新能力;通过万方专利科技资源数据集验证了所提方法的可行性和有效性,为更加全面地挖掘资源文本特征和按需服务实体产业提供了一种新的思路和手段。     

风速时间序列混沌判定方法比较研究

混沌识别是对非线性时间序列进行混沌预测的前提。针对时间序列风速确定性与随机性相结合的复杂非线性特征,研究了不同的混沌识别方法,并对风速时间序列进行混沌特征识别。应用随机噪声、周期运动及经典混沌系统的时间序列对所选方法进行可靠性验证。对美国国家风能研究中心M2测风塔实测时间序列风速数据进行非线性混沌特征识别。结果表明:风速时间序列具有明显的混沌特征;各风速时间序列表现出不同程度的混沌特征;各混沌识别方法对风速时间序列混沌特征的表达形式不同,互为补充,相互验证。     

浮法玻璃熔窑火焰空间石油焦部分替代重油燃烧的数值模拟

针对浮法玻璃熔窑火焰空间建立模型并进行了数值模拟，在保证热值相同的前提下，对比研究了重油燃烧及将石油焦部分替代重油燃烧时的流场分布特征。结果表明，石油焦部分代替重油燃烧后，两种燃料可很好地混合燃烧，窑炉内温度制度基本不受影响；石油焦着火时间比重油长，两种燃料混合燃烧时平均着火点滞后于仅使用重油时，且燃烧路径更长，燃烧时产生了大量CO，整个火焰空间及烟气出口处NOx的平均排放量与仅使用重油相比降低了30.02%，NOx减排效果明显。     

融合环境因素的有限空间毒气扩散危害程度分析

为探究环境因素对毒气扩散危害程度的影响,通过对比有限空间内外环境差异,了解气体在有限空间内受力情况,并以传统高斯烟羽模型为基础,考虑扩散气体与有限空间边界碰撞产生的反射作用,建立了适用于有限空间气体扩散的改进高斯烟羽模型。深度剖析有限空间气体扩散环境,挖掘气体扩散主要关联因子,构建风速、地表粗糙度对有限空间气体扩散的影响函数;参照有限空间环境特征,分别设置3种不同风速与2种不同地表粗糙度,推求6种不同环境条件下气体扩散面积,阐明风速与地表粗糙度对有限空间气体扩散的影响程度。结果表明:在单一风速条件下,风速越高,地表粗糙度越低,洞室内H2S气体滞留时间越短,洞室内气体的扩散面积越小;风速越低,地表粗糙度越高,洞室内气体的扩散面积越大。     

Partitioning of PCBs from air to clothing materials in a Danish apartment

Polychlorinated biphenyl (PCB) contamination of buildings continues to pose an exposure threat, even decades after their application in the form of calks and other building materials. In this research, we investigate the ability of clothing to sorb PCBs from contaminated air and thereby influence exposure. The equilibrium concentration of PCB‐28 and PCB‐52 was quantified for nine used clothing fabrics exposed for 56 days to air in a Danish apartment contaminated with PCBs. Fabric materials included pure materials such as cotton and polyester, or blends of polyester, cotton, viscose/rayon, and/or elastane. Air concentrations were fairly stable over the experimental period, with PCB‐28 ranging from 350 to 430 ng/m³ and PCB‐52 ranging from 460 to 550 ng/m³. Mass accumulated in fabric ranged from below detection limits to 4.5 mg/g of fabric. Cotton or materials containing elastane sorbed more than polyester materials on a mass basis. Mass‐normalized partition coefficients above detection limits ranged from 10^5.7 to 10^7.0 L/kg. Clothing acts as a reservoir for PCBs that extends dermal exposure, even when outside or in uncontaminated buildings.