基于动态行为学习的空中目标识别方法

针对空中移动目标识别问题,提出了一种基于动态行为学习的识别方法。首先,从数据源中提取目标要素,经过标注形成目标数据特征集;其次,基于应用场景进行特征组合,形成特征模型要素;然后,基于深度学习算法进行模型训练,得到评估最优的模型参数;最后,利用训练后的模型进行目标识别处理。通过数值仿真验证,该方法能够有效地识别无业务规则的目标身份。     

Effect of α phase morphology on fatigue crack growth behavior of Ti−5Al−5Mo−5V−1Cr−1Fe alloy

Taking a Ti−5Al−5Mo−5V−1Cr−1Fe alloy as exemplary case, the fatigue crack growth sensitivity and fracture features with various tailored α phase morphologies were thoroughly investigated using fatigue crack growth rate (FCGR) test, optical microscopy (OM) and scanning electron microscopy (SEM). The tailored microstructures by heat treatments include the fine and coarse secondary α phase, as well as the widmanstatten and basket weave features. The sample with coarse secondary α phase exhibits better comprehensive properties of good crack propagation resistance (with long Paris regime ranging from 15 to 60 MPa·m^1/2), high yield strength (1113 MPa) and ultimate strength (1150 MPa), and good elongation (11.6%). The good crack propagation resistance can be attributed to crack deflection, long secondary crack, and tortuous crack path induced by coarse secondary α phase.     

A process fault diagnosis method using multi-time scale dynamic feature extraction based on convolutional neural network

Unlike many other techniques used in process control, which are widely applied in practice and play significant roles, abnormal situation management (ASM) still relies heavily on human experience, not least because the problem of fault detection and diagnosis (FDD) has not been well addressed. In this paper, a process fault diagnosis method using multi-time scale dynamic feature extraction based on convolutional neural network (CNN) consisting of similarity measurement, variable ranking, and multi-time scale dynamic feature extraction is proposed. The CNN-based model containing the fixed multiple sampling (FMS) layer can extract dynamic characteristics of process data at different time scales. The benchmark Tennessee Eastman (TE) process is used to verify the performance of the proposed method.     

Feature-based ontological framework for semantic interoperability in product development

An essential requirement in integrating tasks in product development is to have a seamless exchange of product information through the entire product lifecycle. A key challenge in the integration is the exchange of shape semantics in terms of understandable labels and representations. A unified taxonomy is proposed to represent, classify, and extract shape features. This taxonomy is built using the Domain-Independent Form Feature (DIFF) model as the representation of features. All the shape features in a product model are classified under three main classes, namely, volumetric features, deformation features and free-form surface features. Shape feature ontology is developed using the unified taxonomy, which brings the shape features under a single reasoning framework. One-to-many reasoning framework is presented for mapping semantically equivalent information (label and representation) of the feature to be exchanged to target applications, and the reconstruction of the shape model automatically in that target application. An algorithm has been developed to extract the semantics of shape features and construct the model in the target application. The algorithm developed has been tested for shape models taken from literature and test cases are selected based on variations of topology and geometry. Results of exchanging product information are presented and discussed. Finally, the limitations of the proposed method for exchanging product information are explained.     

长江经济带工业集聚对水环境污染的影响——基于空间计量与门槛效应的检验

经济发展与生态环境动态良性循环已经成为社会经济发展的重要议题。为实现长江经济带高质量发展，以2007—2018年长江经济带11个省市为样本，采用空间计量和面板门槛模型考察工业集聚与水环境污染之间的关系。研究表明：长江经济带各省市水环境污染具有显著的空间自相关性；长江经济带工业集聚水平和水环境污染表现出先降低后增强的“U”形变化特征，说明工业集聚水平对水环境污染的影响存在一个阈值；长江经济带工业集聚产生的规模效应和结构效应对水环境污染存在显著的双门槛效应，在不同的工业集聚水平下，规模效应和结构效应表现出不同的外部性特征；工业集聚产生的技术溢出效应对水环境污染的影响同样具有显著的双门槛作用；随着各地区工业集聚水平的提高，技术溢出效应对水环境污染的减排作用表现出先强后弱的趋势。     

Combined effect of antimicrobial edible coatings with reduction of initial microbial load on the shelf-life of fresh hake (Merluccius merluccius) medallions

Two distinct strategies were combined to preserve fresh fish (Merluccius merluccius) under refrigeration at 4 °C for 12 days: (i) the application of an antimicrobial edible coating enriched with oregano essential oil (OEO) or carvacrol (CV) and (ii) the reduction of initial microbial load by good handling practise and the use of sodium hypochlorite (NaOCl). The action of antimicrobial coatings alone retarded the growth of Enterobacteriaceae, lactic acid bacteria (LAB) and H₂S producing bacteria on fish samples. The reduction of initial microbial load by itself only affected the evolution of LAB, but not the rest of the bacterial groups. When using both techniques combined, edible antimicrobial coatings were significantly more effective with additional and significant delays in the growth of mesophilic, psychrotrophic and Pseudomonas bacteria. Thus, the use of both strategies combined resulted in a reduction of the counts of all bacterial groups after 12 days of storage which ranged from 1.5 log and 8 log, in Pseudomonas and H₂S producing bacteria, respectively. Moreover, no significant differences were observed when comparing the microbiological evolution of samples treated with OEO compared to those only treated with CV.