Synchronous fluorescence and multivariate classification analysis as a screening tool for determining Sudan I dye in culinary spices

Spices are a globally traded commodity which has been found to be adulterated with forbidden Sudan dyes. This work proposes a screening method for determining the adulteration of paprika varieties (mild, hot and smoked) with Sudan I dye, based on constant-wavelength synchronous fluorescence spectroscopy with multivariate classification. Different wavelength-intervals (Δλ) were evaluated. Classification models were built with Partial Least Squares-Discriminant Analysis (PLS-DA) at two Sudan I dye concentration levels (1 and 5 mg L⁻¹) and they were tested with samples at a lower level (0.5 mg L⁻¹). Classification results were quite satisfactory when a strategy based on first-derivative spectra was used for improving classification results. Δλ = 60 nm was chosen as the optimum wavelength interval giving a 100% of sensitivity and specificity. These results are promising because the risk of assigning adulterated samples as safe to be consumed is highly minimized. The proposed method is feasible, rapid and simple taking advantage of Sudan I fluorescence phenomena in a direct way.     

Novel data structure and visualization tool for studying technology evolution based on patent information: The DTFootprint and the TechSpectrogram

We introduce a new, bespoke data structure to analyze and visualize the evolution of a technology. The technology under analysis is defined by a set of patents corresponding to a technical field, owned by a company or invented by a team of research. Our data structure, the Dynamic Technology Footprint –DTFootprint–, facilitates the analysis and visualization of trends and dynamics of a given technology, and therefore the evolution of a technical field, a company, or a team of people. A graphical tool based on our data structure is defined, it is named Technology Spectrogram –TechSpectrogram–, because it is inspired by the acoustic frequency spectrograms: as the acoustic frequency spectrograms visualize the dynamics of an acoustic wave showing the evolution of its frequency components our tool shows the dynamics of a technology showing the evolution of its technological components, which are represented by the whole set of IPC-codes. Our graphical tool, the TechSpectrogram is shown for some study cases, and its application to the history of technology and technology management are disclosed.     

Terrain classification and adaptive locomotion for a hexapod robot Qingzhui

Frontiers of Mechanical Engineering - Legged robots have potential advantages in mobility compared with wheeled robots in outdoor environments. The knowledge of various ground properties and...     

基于kmeans-SVM的二叉树粗分类方法

针对大型数据库中进行匹配识别时存在识别速度慢、时间长、影响实时应用效果的问题,提出了一种树形层次结构的粗分类方法。通过k-means得到两类粗分类的样本,用这两类粗分类数据训练SVM分类器,找到分类超平面,再不断调整分类超平面,最后构建二叉树型结构达到粗分类的目的。三个方法相结合很好地缩小目标的搜索范围,提高了识别时候的效率。     

Reduced chemistries with the Quantemol database (QDB)

Typical feed gas mixtures used in technological and other plasmas may give rise to reaction networks involving several hundred reactions. Such chemistries are often too large to be used in full reactor simulations and it is therefore desirable to construct reduced chemistry networks which mimic as closely as possible the behavior of the full chemistry but employ far fewer individual reactions and species. Constructed chemistries are available from the Quantemol database (QDB) and two approaches to constructing reduced chemistry from these chemistries based on (a) physical intuition and (b) sensitivity analysis of dominant reaction pathways, are explored. In doing this it is necessary to consider different pressure and power regimes. Reduced chemistry sets are presented for CF₄ /O₂/N₂/H₂, for which 396 reactions and 52 species are reduced to 71 reactions and 26 species, and for pure O₂, for which 45 reactions and 10 species are reduced to 34 reactions.     

数据库垄断的成因及对策分析

学术数据库市场被少数几个出版商掌握，新的数据库商难以加入到竞争中来，因此导致了学术数据库市场的垄断问题。本文通过叙述学术数据库垄断的四个问题，即数据库定价的不合理、数据库许可权的滥用、经营者集中和数据库用户受限，提出通过开放获取、图书馆联合与立法保护来应对数据库市场的垄断问题。     

基于声发射和高斯混合模型的灰岩破裂特征识别研究

通过单轴压缩条件下灰岩破裂过程的声发射试验研究,利用高斯混合模型(GMM)对加载过程声发射信号波形特征进行深入分析,探索性识别灰岩破裂失稳过程的裂纹模式及其前兆特征。分析结果表明,灰岩在单轴加载过程中先后主要存在张拉和剪切两种破裂模式。其中,张拉破裂的声发射信号波形特征在AF-RA坐标空间呈现低A_F值、高R_A值分布;剪切破裂的声发射信号波形特征在AF-RA坐标空间呈现低R_A值、高A_F值,且随着应力的增加分布中心向A_F轴靠拢。GMM分析结果揭示了灰岩在整个应力加载过程中以张拉裂纹为主,在加载前中期几乎全为张拉裂纹,临近破坏阶段过渡到剪切破坏为主。剪切裂纹所占比例的最大值出现在(0.8～0.9)σ_c阶段,也是AF-RA坐标轴分布呈现最大A_F值时。研究结果可为预测早期灰岩破裂失稳提供参考,同时为深入研究识别岩石破裂失稳前兆信号特征提供了一种分析方法。     

基于特征选择和深度信念网络的文本情感分类算法

由于人类语言的复杂性，文本情感分类算法大多都存在因为冗余而造成的词汇量过大的问题。深度信念网络（DBN）通过学习输入语料中的有用信息以及它的几个隐藏层来解决这个问题。然而对于大型应用程序来说，DBN是一个耗时且计算代价昂贵的算法。针对这个问题，提出了一种半监督的情感分类算法，即基于特征选择和深度信念网络的文本情感分类算法（FSDBN）。首先使用特征选择方法（文档频率（DF）、信息增益（IG）、卡方统计（CHI）、互信息（MI））过滤掉一些不相关的特征从而使词汇表的复杂性降低；然后将特征选择的结果输入到DBN中，使得DBN的学习阶段更加高效。将所提算法应用到中文以及维吾尔语中，实验结果表明在酒店评论数据集上，FSDBN在准确率方面比DBN提高了1.6%，在训练时间上比DBN缩短一半。     

基于卷积神经网络的构件分类策略的研究

为了提高软件复用过程中构件检索的效率，分析了软件构件分类技术的优缺点以及构件特征，从构件刻面信息的角度，采用卷积神经网络技术，提出一种基于卷积神经网络的构件分类策略；利用卷积神经网络对构件刻面特征进行提取，减少人为因素，提高刻面信息提取精确性，并训练出基于卷积神经网络的构件分类模型，通过具体的实验，来论证该模型的准确性，以达到提高构件检索效率的目的。