One-Dimensional Deep Convolutional Neural Network for Mineral Classification from Raman Spectroscopy

Neural Processing Letters - Raman spectroscopy is often used for the composition determination and rapid classification of materials because it can reflect the molecular information of materials....     

Fractional order battery modelling methodologies for electric vehicle applications: Recent advances and perspectives

Science China Technological Sciences - Accurate modelling of lithium ion batteries is crucial for battery management in electric vehicles. Recent studies have revealed the fractional order nature...     

快速切换(SMED)在空调制造厂的研究与应用

在目前市场需求呈现规模扩张和品类个性化的冲击下,制造业面对的竞争压力愈发明显.且随着新时代自动化、信息化、大数据智能化等先进制造特征的兴起,更加促使制造业向转型升级不断进军.以空调制造业的控制器版块为例,从制约此单位效率的SMT车间切换浪费为切入点,在SMED快速换模的理念基础上,通过使用IE分析工具对切换流程进行研究,提炼出一套多模组固定料站切换模型,同时结合自动化、信息化等智能制造技术引进,完成SMT车间人力投入减少35人,日均产出点数提升18.29％,设备运行率提升15.46％,综合成本降低110.6万元/年的效益.成功推广应用至电子物料拣选版块,并开发信息化看板,夯实应用效益,再次证实"多模组固定料站"快速切换模型是典型小、多、高生产模式,具有可行性的解决方案.     

Human responses to high levels of carbon dioxide and air temperature

In this study, 30 subjects were exposed to different combinations of air temperature (T_a: 24, 27, and 30°C) and CO₂ level (8000, 10 000, and 12 000 ppm) in a high-humidity (RH: 85%) underground climate chamber. Subjective assessments, physiological responses, and cognitive performance were investigated. The results showed that as compared with exposure to T_a = 24°C, exposure to 30°C at all CO₂ levels caused subjects to feel uncomfortably warm and experience stronger odor intensity, while increased mental effort and greater intensity of acute health symptoms were reported. However, no significant effects of T_a on task performance or physiological responses were found. This indicated that subjects had to exert more effort to maintain their performance in an uncomfortably warm environment. Increasing CO₂ from 8000 to 12 000 ppm at all T_a caused subjects to report higher rates of headache, fatigue, agitation, and feeling depressed, although the results were statistically significant only at 24 and 27°C. The text typing performance and systolic blood pressure (SBP) decreased significantly at this exposure, whereas diastolic blood pressure (DBP) and thermal discomfort increased significantly. These effects suggest higher arousal/stress. No significant interaction effect of T_a and CO₂ concentration on human responses was identified.     

An effectiveness analysis of altmetrics indices for different levels of artificial intelligence publications

Scientometrics - Altmetrics indices are increasingly applied to measure scholarly influence in recent years because they can reflect the influence of research outputs more timely comparing with...     

Super-Resolution Reconstruction of Images Based on Microarray Camera

In the field of images and imaging, super-resolution (SR) reconstruction of images is a technique that converts one or more low-resolution (LR) images into a highresolution (HR) image. The classical two types of SR methods are mainly based on applying a single image or multiple images captured by a single camera. Microarray camera has the characteristics of small size, multi views, and the possibility of applying to portable devices. It has become a research hotspot in image processing. In this paper, we propose a SR reconstruction of images based on a microarray camera for sharpening and registration processing of array images. The array images are interpolated to obtain a HR image initially followed by a convolution neural network (CNN) procedure for enhancement. The convolution layers of our convolution neural network are 3×3 or 1×1 layers, of which the 1×1 layers are used to improve the network performance particularly. A bottleneck structure is applied to reduce the parameter numbers of the nonlinear mapping and to improve the nonlinear capability of the whole network. Finally, we use a 3×3 deconvolution layer to significantly reduce the number of parameters compared to the deconvolution layer of FSRCNN-s. The experiments show that the proposed method can not only ameliorate effectively the texture quality of the target image based on the array images information, but also further enhance the quality of the initial high resolution image by the improved CNN.     

Densification mechanism during reactive hot pressing of B4C-ZrO2 mixtures

The densification behaviors of pure B₄C and B₄C-ZrO₂ mixtures were compared during hot pressing. The results showed that in-situ formed ZrB₂ effectively enhanced the densification process of B₄C-ZrO₂ mixtures, more significantly during the intermediate stage. Within the relative density ranging from 0.75 to 0.90, the B₄C-15?wt%ZrO₂ mixture (B15Z) achieved the maximum densification rate as twice much as that of pure B₄C. The stress exponent n>3 indicated plastic deformation was the dominant densification mechanism of B15Z. The viscosities of plastic flow were evaluated using Murray-Rodger-William equation and the viscosity of B15Z was only a quarter of that in pure B₄C. The sintering activation energy was calculated to be 305.9?kJ/mol for pure B₄C and 197?kJ/mol for B15Z, respectively. It was proposed that the lower viscosity of plastic flow and activation energy accelerated the sliding and propagating motions of plastic flow, by which underlain the enhanced densification behaviors of B₄C-ZrO₂ mixtures.