LinkingPark: An automatic semantic table interpretation system

In this paper, we present LinkingPark, an automatic semantic annotation system for tabular data to knowledge graph matching. LinkingPark is designed as a modular framework which can handle Cell-Entity Annotation (CEA), Column-Type Annotation (CTA), and Columns-Property Annotation (CPA) altogether. It is built upon our previous SemTab 2020 system, which won the 2nd prize among 28 different teams after four rounds of evaluations. Moreover, the system is unsupervised, stand-alone, and flexible for multilingual support. Its backend offers an efficient RESTful API for programmatic access, as well as an Excel Add-in for ease of use. Users can interact with LinkingPark in near real-time, further demonstrating its efficiency.     

英国食品GDAs标签的发展经验及对中国的启发

对英国食品每日摄入量指南（GDAs）标签开展案例研究，结果发现，GDAs标签从包装背面标签转为FOP标签，实施已有20年以上。该标签采用特定营养素体系度量法模型，显示每份食品能量、糖、脂肪、饱和脂肪、盐的含量及其每日参考摄入量占比，既没有颜色编码又没有形象的图标显示，且实施效果不如多数FOP标签。对此，中国可考虑将营养成分表信息以食品份量单位直观显示在包装正面，方便消费者关注与理解。     

Full scale investigation of GCL damage mechanisms in small earth dam retrofit applications under earthquake loading

This paper reports results of full scale testing to further explore potential GCL damage mechanisms in earth dam retrofit applications in seismically active areas; in particular, to a) investigate whether shear displacements could reduce the magnitude of GCL panel overlap during earthquake shaking; b) explore the influence of gravel particles on GCL thickness at localised point of contact; and c) observe the consequences of an accidental exposure of an uncovered GCL to short duration rainfall in terms of moisture content and effects during subsequent compaction. The results of these experiments indicate that even under severe shaking no movements were detected at the GCL panel overlap. Whereas gravel particles were observed to locally reduce the thickness of the GCL to 2.2 mm, no plowing of the particle into the GCL occurred due to a lack of shear displacement at the interface, resulting in no localised internal erosion through the barrier. Furthermore, hydration of GCL panels during construction due to surface wetting was observed to result in a state of hydration less than its post-construction state. These results indicate that although each of the three GCL damage mechanisms cannot be ruled out to ever be relevant in practice, the performance of the GCL retrofitted earth dam tested was satisfactory under even severe Level 2 earthquake shaking, and suggests that the retrofitting of small earth dams with GCLs is a promising strategy to improve their static and seismic resistance.     

LPNN-based approach for LASSO problem via a sequence of regularized minimizations

In compressive sampling theory, the least absolute shrinkage and selection operator (LASSO) is a representative problem. Nevertheless, the non-differentiable constraint impedes the use of Lagrange programming neural networks (LPNNs). We present in this article the -LPNN model, a novel algorithm that tackles the LASSO minimization together with the underlying theory support. First, we design a sequence of smooth constrained optimization problems, by introducing a convenient differentiable approximation to the non-differentiable -norm constraint. Next, we prove that the optimal solutions of the regularized intermediate problems converge to the optimal sparse signal for the LASSO. Then, for every regularized problem from the sequence, the -LPNN dynamic model is derived, and the asymptotic stability of its equilibrium state is established as well. Finally, numerical simulations are carried out to compare the performance of the proposed -LPNN algorithm with both the LASSO-LPNN model and a standard digital method.     

基于分段加权的反向稀疏跟踪算法研究

为提高稀疏表示跟踪模型性能，提出一种分段加权的反向稀疏跟踪算法，将跟踪问题转化为在贝叶斯框架下寻找概率最高的候选对象问题，构造不同的分段权重函数来分别度量候选目标与正负模板的判别特征系数。通过池化来降低跟踪结果的不确定性干扰，选择正负模板加权系数差值最大的候选表示作为跟踪结果。实验表明，在光照变化、遮挡、快速运动、运动模糊情况下，所提出的算法可以确保跟踪结果的准确性和鲁棒性。     

陕北沙漠区浅埋厚煤层开采潜水位及生态响应

煤炭开采造成上覆岩层破裂、移动，破坏了矿区含（隔）水层结构，改变了地表水及地下水循环演化状态，对浅表层生态环境造成严重影响，引发一系列环境地质问题。为深入研究沙漠地区厚煤层开采给潜水位及生态环境造成的影响，以毛乌素沙漠金鸡滩矿为例，对水文地质条件进行了研究，采用数值模拟的方法，模拟了沙漠区厚煤层开采潜水位的变化，并通过采动潜水位监测数据验证了预测结果。调查分析了研究区及周边地表生态环境现状，预测采后潜水位基本满足植物生长需求，对生态环境影响不大。     

精密磨床转台静压轴承的强健化设计

针对精密磨床转台静压轴承性能仿真数据与其回转精度实测数据不一致的问题，为提高转台静压轴承的设计水平，提出了静压轴承的强健化设计方法。该方法考虑了轴承结构参数在轴承全生命周期内的变化，分析了半径间隙、油腔尺寸、节流比及润滑油黏度在设计、加工、装配和服役4个阶段的变化规律，重点研究了半径间隙在各阶段对轴承性能造成的影响，给出了转台静压轴承的强健化设计流程。通过一个径向轴承的设计实例对该强健化设计方法进行了说明，并将设计结果与传统设计进行了对比。对比的指标是轴承在4个阶段的刚度、承载力和温升，这3个指标对轴承回转精度有直接影响。研究表明：进行强健化设计后，在生命周期内静压轴承的刚度和承载力的变化量为10%~27%，温度的变化量为0.5%~1.6%，较传统设计更能保证转台回转精度的稳定。     

多共振分量融合CNN的行星齿轮箱故障诊断

针对行星齿轮箱中各部件所激起的振动成分混叠、早期故障特征经常被较强的各级齿轮谐波成分以及环境噪声所湮没的问题，提出一种多共振分量融合卷积神经网络（multi-resonance component fusion based convolutional neural network，简称MRCF-CNN）的行星齿轮箱故障诊断方法。首先，对振动信号进行共振稀疏分解，得到包含齿轮谐波成分的高共振分量和可能包含轴承故障冲击成分的低共振分量；其次，构建多共振分量融合卷积神经网络，将得到的高、低共振分量和原始振动信号进行自适应的特征级融合，通过有监督的方式训练模型并进行行星齿轮箱故障诊断。对行星齿轮箱实验数据的分析结果表明，该方法能够有效分类行星齿轮箱中滚动轴承和齿轮的故障，成功对行星齿轮箱故障进行诊断，同时能够进一步增强卷积神经网络对振动信号所蕴含的故障信息的辨识能力。     

实用型气动旋转装夹工作台的设计

该设计实例为一种气动旋转装夹工作台,详细介绍该装置的设计思路,分析其结构和动作原理。该装置在实际应用中,完全满足了特殊工况需求,性能稳定,具有一定的推广价值。