Feature selection methods for root-cause analysis among top-level product attributes

Manufacturing companies not only strive to deliver flawless products but also monitor product failures in the field to identify potential quality issues. When product failures occur, quality engineers must identify the root cause to improve any affected product and process. This root-cause analysis can be supported by feature selection methods that identify relevant product attributes, such as manufacturing dates with an increased number of product failures. In this paper, we present different methods for feature selection and evaluate their ability to identify relevant product attributes in a root-cause analysis. First, we compile a list of feature selection methods. Then, we summarize the properties of product attributes in warranty case data and discuss these properties regarding the challenges they pose for machine learning algorithms. Next, we simulate datasets of warranty cases, which emulate these product properties. Finally, we compare the feature selection methods based on these simulated datasets. In the end, the univariate filter information gain is determined to be a suitable method for a wide range of applications. The comparison based on simulated data provides a more general result than other publications, which only focus on a single use case. Due to the generic nature of the simulated datasets, the results can be applied to various root-cause analysis processes in different quality management applications and provide a guideline for readers who wish to explore machine learning methods for their analysis of quality data.     

Theoretical estimation of dielectric loss of oxide glasses using nonequilibrium molecular dynamics simulations

To theoretically explore amorphous materials with a sufficiently low dielectric loss, which are essential for next-generation communication devices, the applicability of a nonequilibrium molecular dynamics simulation employing an external alternating electric field was examined using alkaline silicate glass models. In this method, the dielectric loss is directly evaluated as the phase shift of the dipole moment from the applied electric field. This method enabled us to evaluate the dielectric loss in a wide frequency range from 1 GHz to 10 THz. It was observed that the dielectric loss reaches its maximum at a few THz. The simulation method was found to qualitatively reproduce the effects of alkaline content and alkaline type on the dielectric loss. Furthermore, it reasonably reproduced the effect of mixed alkalines on the dielectric loss, which was observed in our experiments on sodium and/or potassium silicate glasses. Alkaline mixing was thus found to reduce the dielectric loss.     

Preparation of Pt/Ce–Zr–Y mixed oxide/anodized aluminium oxide catalysts for hydrogen passive autocatalytic recombination

The use of a Pt-based catalyst was evaluated for autocatalytic hydrogen recombination. The Pt was supported on a mixture of Ce-, Zr- and Y-oxides (CZY) to yield nanosized Pt particles. The Pt/CZY/AAO catalyst was then prepared by the spray-deposition of the Pt/CZY intermediate onto an anodized aluminium oxide (AAO) layer on a metallic aluminum core. The Pt/CZY/AAO catalyst (3 × 1 cm) was evaluated for hydrogen combustion (1–8 vol% hydrogen in the air) in a recombiner section testing station. The thermal distribution throughout the catalyst surface was investigated using an infrared camera. The maximum temperature gradient (ΔT) for the examined hydrogen concentrations did not exceed 36 °C. The Pt/CZY/AAO catalyst was also evaluated for prolonged hydrogen combustion duration to assess its durability. An average combustion temperature of 239.0 ± 10.0 °C was maintained for 53 days of catalytic hydrogen combustion, suggesting that there was limited, or no, catalyst deactivation. Finally, a Pt/CZY/AAO catalytic plate (14.0 × 4.5 cm) was prepared to investigate the thermal distribution. An average surface temperature of 212.5 °C and a maximum ΔT of 5.4 °C was obtained throughout the catalyst surface at a 3 vol% hydrogen concentration.     

自适应融合层级特征的混合退化图像复原算法

多种退化类型混合的图像比单一类型的退化图像降质更严重,很难建立精确模型对其复原,研究端到端的神经网络算法是复原的关键.现有的基于操作选择注意力网络的算法(operation-wiseattentionnetwork,OWAN)虽然有一定的性能提升,但是其网络过于复杂,运行较慢,复原图像缺乏高频细节,整体效果也有提升的空间.针对这些问题,提出一种基于层级特征融合的自适应复原算法.该算法直接融合不同感受野分支的特征,增强复原图像的结构;用注意力机制对不同层级的特征进行动态融合,增加模型的自适应性,降低了模型冗余;另外,结合L1损失和感知损失,增强了复原图像的视觉感知效果.在DIV2K,BSD500等数据集上的实验结果表明,该算法无论是在峰值信噪比和结构相似性上的定量分析,还是在主观视觉质量方面,均优于OWAN算法,充分证明了该算法的有效性.     

Tactile colour pictogram to improve artwork appreciation of people with visual impairments

A recent development in tactile technology enables an improvement in the appreciation of the visual arts for people with visual impairment (PVI). The tactile sense, in conjunction with, or a possibly as an alternative to, the auditory sense, would allow PVIs to approach artwork in a more self‐driven and engaging way that would be difficult to achieve with just an auditory stimulus. Tactile colour pictograms (TCPs), which are raised geometric patterns, are ideographic characters that are designed to enable PVIs to identify colours and interpret information by touch. In this article, three TCPs are introduced to code colours in the Munsell colour system. Each colour pattern consists of a basic cell size of 10 mm × 10 mm to represent the patterns consistently in terms of regular shape. Each TCP consists of basic geometric patterns that are combined to create primary, secondary, and tertiary colour pictograms of shapes indicating colour hue, intensity and lightness. Each TCP represents 29 colours including six hues; they were then further expanded to represent 53 colours. Two of them did not increase the cell size, the other increased the cell size 1.5 times for some colours, such as yellow‐orange, yellow, blue, and blue‐purple. Our proposed TCPs use a slightly larger cell size compared to most tactile patterns currently used to indicate colour, but code for more colours. With user experience and identification tests, conducted with 23 visually impaired adults, the effectiveness of the TCPs suggests that they were helpful for the participants.     

谈陶瓷装饰中的婴戏纹饰与西方艺术品中的儿童形象

婴戏纹饰即描绘儿童游戏时的画作,是中国人物画的一种,更是陶瓷装饰中常见的传统题材。其主要以儿童为主要绘画对象,表现儿童纯真,或借以其他物象,组成吉祥图案,在我国陶瓷绘画上广泛运用,有着深刻的社会形态特征和思想文化的背景。其始于唐代,兴盛于宋金,明清两朝日臻成熟,并延续至今。在西方艺术史当中,儿童形象大都通过神话人物或宗教相关的艺术品走进人们视野,用以表现某些宗教思想或精神诉求。本文主要探讨陶瓷婴戏纹饰在我国历史发展历程中的演变概况,以及笔者对我国陶瓷婴戏纹饰和西方艺术品中儿童形象横向对比下的一些思考。     

硫磷混合酸溶样重铬酸钾容量法测定全铁

介绍了硫磷混合酸溶样重铬酸钾容量法测定矿石中铁含量的方法和步骤。重点讨论了一线生产中的质量控制。     

Evolutionary collective behavior decomposition model for time series data mining

In this research, we propose a novel framework referred to as collective game behavior decomposition where complex collective behavior is assumed to be generated by aggregation of several groups of agents following different strategies and complexity emerges from collaboration and competition of individuals. The strategy of an agent is modeled by certain simple game theory models with limited information. Genetic algorithms are used to obtain the optimal collective behavior decomposition based on history data. The trained model can be used for collective behavior prediction. For modeling individual behavior, two simple games, the minority game and mixed game are investigated in experiments on the real-world stock prices and foreign-exchange rate. Experimental results are presented to show the effectiveness of the new proposed model.     

镁改性活性炭强化活性污泥处理混合污水研究

基于序批式活性污泥法(SBR)工艺,将镁盐改性活性炭(MgO-PAC)与传统活性炭(PAC)混合而成MPAC材料,用于处理生活与工业混合污水。通过连续30 d的运行实验,探讨了MPAC材料对生活与工业混合污水中COD、NH4^+-N和TP的去除效果以及对污泥的比耗氧速率、沉降性能和微生物多样性的影响。结果表明,投加MPAC材料对污水中COD的去除率提升了12.7百分点,对TP的去除率提升了17.5百分点,对NH4^+-N的去除率超过86.4%。投加MPAC后处理效果更好的重要原因,在于MPAC使得活性污泥的沉降性能和比耗氧速率得到明显改善,也提升了污泥的微生物丰度。MPAC对活性污泥处理生活与工业混合污水具有强化作用。