奉御董造与禁廷制样:两宋地方官窑执行的御用瓷设计制度

宋朝兴起的地方官窑为宫廷烧造御用瓷是官手工业发展的亮点之一,并逐步形成了两宋地方官窑执行的御用瓷设计制度,设计制度形成绝非偶然,它是宋朝强化皇权意志、器用制度与地方精湛制瓷工艺共同作用的结果。地方官窑主要执行有奉御董造制度、禁廷制样制度。体现的御用瓷设计制度特征十分明显:前期是指专门接受宫廷敕命,由专官管理,奉御烧造宫廷各种用瓷,有命则供,否则止;后期是指宫廷对御用瓷有专门的设计图式,特由礼部礼制局彩画制样后,向地方官窑降发图样烧造御用瓷。尤其是地方官窑执行的禁廷制样须索制度为明代御器厂和清代御窑厂所继承。     

Failure load prediction and optimisation for adhesively bonded joints enabled by deep learning and fruit fly optimisation

Adhesively bonded joints have been extensively employed in the aeronautical and automotive industries to join thin-layer materials for developing lightweight components. To strengthen the structural integrity of joints, it is critical to estimate and improve joint failure loads effectually. To accomplish the aforementioned purpose, this paper presents a novel deep neural network (DNN) model-enabled approach, and a single lap joint (SLJ) design is used to support research development and validation. The approach is innovative in the following aspects: (i) the DNN model is reinforced with a transfer learning (TL) mechanism to realise an adaptive prediction on a new SLJ design, and the requirement to re-create new training samples and re-train the DNN model from scratch for the design can be alleviated; (ii) a fruit fly optimisation (FFO) algorithm featured with the parallel computing capability is incorporated into the approach to efficiently optimise joint parameters based on joint failure load predictions. Case studies were developed to validate the effectiveness of the approach. Experimental results demonstrate that, with this approach, the number of datasets and the computational time required to re-train the DNN model for a new SLJ design were significantly reduced by 92.00% and 99.57% respectively, and the joint failure load was substantially increased by 9.96%.     

Automated coronal hole segmentation from Solar EUV Images using the watershed transform

Region of interest segmentation in solar images is the subject of frequent research in solar physics. This study outlines watershed by immersion segmentation to identify coronal hole areas in solar images acquired using the Extreme UV Imaging Telescope (EIT). Solutions presented here produce highly accurate segmentation results of coronal holes of irregular shape, and what is more, they do so for images representing varied solar activity, recorded in different years and months. In addition, the solutions presented here make all the methods used operate very quickly. These methods include: the preprocessing step before the watershed segmentation, the watershed segmentation itself, and also the postprocessing of solar images after the watershed segmentation. The mean duration of the entire segmentation process of solar images amounts to 342 ms for a single coronal hole, without the parallel implementation of the methods used. The experiments were carried out on a computer with an Intel Core i7 CPU @ 2 GHz and 4 GB RAM. After the seed point is identified inside the coronal hole, the segmentation runs automatically.     

Ermittlung von Verfahrensgrenzen für das Fügen durch Knickbauchen anhand des Werkstoffes E235+N

Through a systematic approach and the consistent comparison of the results between experimental and numerical investigations, a deep understanding of the bulging mechanisms has been first developed. From these investigations process limitations were derived and presented in the form of a working diagram for the material E235+N. With regard to a wide industrial use of upset bulging as a joining technology, a technologically, productively as well as economically appropriate method could be developed and validated by means of practical and numerical experiments.     

Short term stock selection with case-based reasoning technique

Stock selection is an important decision making problem. Trading strategies and rules based on fundamental and technical analysis can be used for decision making process. In this paper, we propose an intelligent stock selection method, which is called case-based reasoning (CBR). This technique uses the fundamental and technical indicators to identify the winning stocks around the earning announcements. CBR method is compared with other artificial intelligence techniques such as multi layer perceptron (MLP), decision trees (QUEST, Classification and Regression Trees, C5), generalized rule induction (GRI) and logistic regression. We show that the performance of CBR is better than the performance of other techniques in terms of classification accuracy, average return, Sharpe ratio and ideal profit.     

一种基于证据推理的视频运动目标融合检测算法

为了解决复杂场景下传统的运动目标检测问题, 利用证据推理—–谨慎有序加权平均方法(COWA-ER), 提出一种综合使用混合高斯、均值滤波和码本的多方法融合的检测方法. 该融合检测算法以上述3 种检测方法为准则建立一个多准则决策框架, 通过双阈值检测法来表征检测过程中的不确定性, 最终利用COWA-ER 方法进行决策级融合, 实现多种方法的优势互补. 实验表明, 所提出的融合检测算法具有更理想的目标检测效果, 能有效应对诸如阴影及光照突变等问题对检测性能的影响.

     

Role of activated carbon on micropollutans degradation by ionizing radiation

The objective of this study was to analyze the influence of the presence of activated carbon on the degradation of the triiodinated contrast medium diatrizoate (DTZ) by the simultaneous use of gamma radiation and activated carbon. Four commercial activated carbons (Ceca, Witco, Sorbo, and Merck) with different textural and chemical characteristics were used for this purpose. The percentage DTZ removal obtained was considerably higher with the gamma radiation/activated carbon (GM/AC) system than with radiolysis in the absence of activated carbon, and it depended on the specific activated carbon employed. First, we optimized the amount of activated carbon required to maximize the amount of DTZ removed by the GM/AC system (0.06 g). The degradation constants were higher with the GM/AC system than with radiolysis alone, evidencing a synergic effect that favors pollutant removal. This synergic effect is independent of the textural but not the chemical characteristics of the activated carbon, observing a higher synergic activity for carbons with a higher surface content of oxygen, specifically quinone groups. We also highlight that the synergic effect of the activated carbon requires adsorbent–adsorbate electrostatic interaction and is absent when this interaction is hindered.     

Atom transfer radical polymerization (ATRP): A versatile and forceful tool for functional membranes

The progress in atom transfer radical polymerization (ATRP) provides an effective means for the design and preparation of functional membranes. Polymeric membranes with different macromolecular architectures applied in fuel cells, including block and graft copolymers are conveniently prepared via ATRP. Moreover, ATRP has also been widely used to introduce functionality onto the membrane surface to enhance its use in specific applications, such as antifouling, stimuli-responsive, adsorption function and pervaporation. In this review, the recent design and synthesis of advanced functional membranes via the ATRP technique are discussed in detail and their especial advantages are highlighted by selected examples extract the principles for preparation or modification of membranes using the ATRP methodology.     

除油脱氮+A~2/O+深度处理的综合工艺处理针状焦污水

采用除油脱氮+A2/O+深度处理的综合工艺处理针状焦生产废水达到《山东省南水北调沿线水污染物综合排放标准》(山东省地方标准DB 37/599-2006)排放标准。     

学生自主命题在教学中的实践

根据酶工程课程的特点,在某些章节教学中采取了学生自主命题、自我考察的方式。文章主要介绍了这种教学实践的实施方案,对实施结果进行总结,并分析其特点,为进一步改进提供了依据。