Structure-sensitive semantic matching for aggregate question answering over knowledge base

Aggregate question answering essentially returns answers for given questions by obtaining query graphs with unique dependencies between values and corresponding objects. Word order dependency, as the key to uniquely identify dependency of the query graph, reflects the dependencies between the words in the question. However, due to the semantic gap caused by the expression difference between questions encoded with word vectors and query graphs represented with logical formal elements, it is not trivial to match the correct query graph for the question. Most existing approaches design more expressive query graphs for complex questions and rank them just by directly calculating their similarities, ignoring the semantic gap between them. In this paper, we propose a novel Structure-sensitive Semantic Matching(SSM) approach that learns aligned representations of dependencies in questions and query graphs to eliminate their gap. First, we propose a cross-structure matching module to bridge the gap between two modalities(i.e., textual question and query graph). Then, we propose an entropy-based gated AQG filter to remove the structural noise caused by the uncertainty of dependencies. Finally, we present a two-channel query graph representation that fuses the semantics of abstract structure and grounding content of the query graph explicitly. Experimental results show that SSM could learn aligned representations of questions and query graphs to eliminate the gaps between their dependencies, and improves up to 12% (F1 score) on aggregation questions of two benchmark datasets.     

Electrochemical Quantification of Neurotransmitters in Single Live Cell Vesicles Shows Exocytosis is Predominantly Partial

Exocytosis plays an essential role in the communication between cells in the nervous system. Understanding the regulation of neurotransmitter release during exocytosis and the amount of neurotransmitter content that is stored in vesicles is of importance, as it provides fundamental insights to understand how the brain works and how neurons elicit a certain behavior. In this minireview, we summarize recent progress in amperometric measurements for monitoring exocytosis in single cells and electrochemical cytometry measurements of vesicular neurotransmitter content in individual vesicles. Important steps have increased our understanding of the different mechanisms of exocytosis. Increasing evidence is firmly establishing that partial release is the primary mechanism of release in multiple cell types.     

Categorical observers for metamerism

A method is proposed to generate categorical colour observer functions (individual colour matching functions) for any field size based on the CIE 2006 system of physiological observer functions. The method combines proposed categorical observer techniques of Sarkar et al with a physiologically-based individual observer model of Asano et al and a clustering technique to produce the optimal set of categorical observers. The number of required categorical observers varies depending on an application with as many as 50 required to predict individual observers' matches when a laser projector is viewed. However, 10 categorical observers are sufficient to represent colour-normal populations for personalized colour imaging. The proposed and recommended categorical observers represent a robust and inclusive technique to examine and quantify observer metamerism in any application of colorimetry.     

Stereo matching cost computation based on nonsubsampled contourlet transform

A new matching cost computation method based on nonsubsampled contourlet transform (NSCT) for stereo image matching is proposed in this paper. Firstly, stereo image is decomposed into high frequency sub-band images at different scales and along different directions by NSCT. Secondly, by utilizing coefficients in high frequency domain and grayscales in RGB color space, the computation model of weighted matching cost between two pixels is designed based on the gestalt laws. Lastly, two types of experiments are carried out with standard stereopairs in the Middlebury benchmark. One of the experiments is to confirm optimum values of NSCT scale and direction parameters, and the other is to compare proposed matching cost with nine known matching costs. Experimental results show that the optimum values of scale and direction parameters are respectively 2 and 3, and the matching accuracy of the proposed matching cost is twice higher than that of traditional NCC cost.     

红外光谱法用于快速测定车用柴油酸度等性质的研究

针对车用柴油酸度等性质测定过程繁琐，采用衰减全反射样品池测定车用柴油的红外光谱，用偏最小二乘法（PLS）建立红外光谱测定车用柴油酸度、密度、闪点和凝点的4个校正模型，验证标准误差分别为0.46 mg/(100 mL),0.77kg/m3,2.60 ℃,2.77 ℃，该方法符合标准方法再现性要求。与标准方法相比，该方法具有无需预处理、操作简单、测量快速、重复性好等优点。     

基于加速度计的坐标系匹配方法研究

为了提高加速度计应用中坐标系的匹配精度,提出了基于加速度计的坐标系匹配方法,介绍了其基本原理,并对加速度计的测角方法进行了深入研究.试验结果表明:该方法测量最大误差≤0.3°,满足实际应用要求,有效地解决了加速度计应用中的坐标系匹配问题.     

基于PC机群的大地电磁Occam反演并行计算研究

Occam反演以其稳定收敛和不依赖于初始模型的特性被广泛应用于大地电磁数据的处理，但偏导数矩阵的计算和拉格朗日乘子的求取导致大量的模型正演，使得反演速度较低。为此，研究了用基于PC机群的并行计算来解决这一问题的方法。首先对Occam反演方法进行了阐述；然后，分析了反演方法中各计算耗费的时间，提出对约占计算量90％的偏导数和拉格朗日乘子进行并行计算的思想，即偏导数计算采用频点计算一级的大粒度并行，拉格朗日乘子扫描和一维搜索分别采用弘值计算一级的大粒度并行和频点计算一级的小粒度并行；给出了并行计算的实现方法，即在PC机群上，利用主一从编程模式实现Occam反演的整体并行计算。在计算中，采用任务组合方式，减少了通信量，较好地实现了负载均衡。在4节点PC机群上，对应于拉格朗日乘子的扫描和一维搜索方式，整体加速比分别达到3．36和2．83。     

人工免疫原理在网络入侵检测系统中的研究

文章分析了人工免疫系统的原理,简单建立了一种基于否定选择算法的网络入侵检测系统,引入了一种用于异常事件识别的r-字符块匹配规则,并对规则存在的漏洞进行了分析。