A novel method based on convolutional neural networks for deriving standard 12-lead ECG from serial 3-lead ECG

Frontiers of Information Technology & Electronic Engineering - Reconstruction of a 12-lead electrocardiogram (ECG) from a serial 3-lead ECG has been researched in the past to satisfy the need...     

基于UG的正交车铣加工回转体表面微观残留仿真

正交车铣加工的回转体表面由铣刀与工件的复合相对运动形成,其形成机理独特,多个参数影响其表面微观形貌。为研究切削参数对正交车铣回转体表面微观残留的影响,基于UG建立了正交车铣回转体表面的仿真加工方法,并通过Vericut构建了虚拟五轴车铣加工环境,由此仿真研究了周向每齿进给量对正交车铣回转体表面微观残留的影响,发现已加工表面微观残留高度随周向每齿进给量增加显著增大。     

PET的紫外老化性能及机理研究

采用力学、紫外-可见光分析和热失质等测试手段研究了PET改性料的紫外老化性能及老化机理。结果表明:复合助剂的加入能显著提升体系的力学性能保持率,进而提升其紫外老化寿命,提升的幅度随复合助剂中耐紫外剂含量的增加而显著增加。DSC分析表明,随着复合助剂的引入和老化的进行,改性料结晶度增加。文中进一步讨论了PET改性料的紫外老化机理。紫外-可见光分析表明,紫外老化能产生醌类和双醌类物质,进而提升PET改性料的紫外吸收度。     

不同有机物对硝酸盐氮测试的影响

研究了红糖、葡萄糖、乙酸钠、甲醇、乙醇、乙酸、丙酸、丁酸、正戊酸、混合有机溶剂等10种不同有机物对麝香草酚光谱法和离子色谱法测试硝酸盐氮的影响。结果表明,溶液中含有红糖或葡萄糖时,均会对麝香草酚法测试硝酸盐氮造成影响,使得测试结果偏大;在无硝酸根离子存在时,红糖和葡萄糖的质量浓度与硝酸盐氮的测试浓度非线性相关;而乙酸钠、甲醇、乙醇、乙酸、丙酸、丁酸、正戊酸和混合有机溶剂则对麝香草酚法测试硝酸盐氮没有影响。实验发现,红糖和葡萄糖在浓硫酸的作用下与麝香草酚发生Molisch反应,形成有色复合物和红棕色不溶性沉淀。实验采用离子色谱法测试硝酸盐氮时,红糖和葡萄糖等糖类有机物对测试结果均无影响。     

双信号金纳米簇对三硝基甲苯的荧光分析

三硝基甲苯作为硝基芳香化合物的代表物,应用相当广泛。其对人体健康、生活环境均具有较大的危害,因此发展简单、便捷检测三硝基甲苯的分析方法非常有必要。利用环境友好的牛血清白蛋白和2-氨基嘌呤合成了双信号金纳米簇荧光探针,基于三硝基甲苯对金纳米簇荧光的淬灭作用,建立了一种检测三硝基甲苯的荧光分析新方法,检出限可达0.14μmol/L,该方法具有良好的灵敏度和选择性。     

Personality expression and recognition in Chinese language usage

User Modeling and User-Adapted Interaction - Personality plays a pivotal role at work. Many scholars have investigated the association between personality and language usage habits in the English...     

Anchoring single Pt atoms on hollow Ag3VO4 spheres for improved activity towards photocatalytic H2 evolution reaction

The high cost of noble metal catalysts has been a great bottleneck for the catalyst industry. Using the noble metal at a single-atom level for catalytic applications could dramatically decrease the cost. The impacts of single Pt atoms on the photocatalytic performance of Ag₃VO₄ have been investigated and reported. In this report, single Pt atoms were anchored on the surface of Ag₃VO₄ (AVO) as a cocatalyst, and the resultant composite photocatalyst has been studied for photocatalytic H₂ production from water driven by visible light. The as-prepared AVO particles are hollow nanospheres in the monoclinic phase with a bandgap of 2.20 eV. The light absorption edge of AVO/Pt is slightly red-shifted compared to that of the pristine AVO, indicating more visible light absorption of AVO/Pt. The XPS peaks of Ag, V, and Pt exhibit a significant shift after AVO and Pt get into contact, suggesting the strong interaction between the surface Ag and V atoms, and single Pt atoms. After 3-h illumination, the photocatalytic H₂ evolution amount from AVO/Pt is improved up to 1400 μmol, which is 2.8 times that on the bare AVO. Such efficient photocatalytic H₂ evolution on AVO/Pt is still maintained after five reaction cycles. The better photocatalytic performance of AVO/Pt has been attributed to the more efficient visible light utilization and the lower interfacial charge transfer resistance, as demonstrated in the DRS and EIS spectra. The presence of the surface Pt atoms also leads to a higher amount of reactive radicals, which could efficiently promote the surface redox reactions.     

基于密集神经网络的灰度图像着色算法

针对在灰度图像着色领域中，传统算法信息提取率不高、着色效果不理想的问题，提出了基于密集神经网络的灰度图像着色算法，以实现改善着色效果，让人眼更好地观察图片信息的目的。利用密集神经网络的信息提取高效性，构建并训练了一个端到端的深度学习模型，对图像中的各类信息及特征进行提取。训练网络时与原图像进行对比，以逐渐减小网络输出结果的信息、分类等各类型的损失。训练完成后，只需向网络输入一张灰度图片，即可生成一张颜色饱满、鲜明逼真的彩色图片。实验结果表明，引入密集网络后，可有效改善着色过程中的漏色、细节信息损失、对比度低等问题，所提算法着色效果较基于VGG网络及U-Net、双流网络结构、残差网络（ResNet）等性能优异的先进着色算法而言取得了显著的改进。     

一种基于Spark的不确定数据集频繁模式挖掘算法

如何在海量不确定数据集中提高频繁模式挖掘性能是目前研究的热点.传统算法大多是以期望、概率或者权重等单一指标为数据项集支持度，在大数据背景下，同时考虑概率和权重支持度的算法难以兼顾其执行效率.为此，本文提出一种基于Spark的不确定数据集频繁模式挖掘算法（UWEFP），首先，为了同时兼顾数据项的概率和权重，计算一项集的最大概率权重值并进行剪枝；然后，为了减少对数据集的多次扫描，结合Spark框架的优点，设计了一种具有FP-tree特征的新颖的UWEFP-tree结构进行模式树的构建及挖掘；最后在Spark环境下，以UCI数据集进行实验验证.实验结果表明本文的方法在保证挖掘结果的同时，提高了效率.