Shell煤气化制甲醇项目之变换装置技术改造与高负荷运行

介绍了Shell煤气化制化制甲醇项目变换装置工艺流程;分析了变换装置高负荷运行时存在的问题;简述了变换装置的技改方案和措施。结果表明,变换炉出口CO含量以及催化剂床层热点温度均可控制在正常范围,均能满足高负荷生产运行的要求。同时,变换装置蒸汽用量大幅降低,催化剂使用寿命大为延长。     

DNCA型氨合成催化剂应用总结

介绍了氨合成工艺流程和设备配置，论述了DNCA型氨合成催化剂的物理特性和应用情况，详细阐述了DNCA催化剂的装填要领、升温还原方案及注意事项，结合生产运行工艺指标和操作控制要点，对DNCA催化剂使用效果进行了总结。     

乌鲁木齐河综合自动化系统工程综述

为解决原有乌鲁木齐河上水利工程老化，自动化管理水平低，水量平衡误差大等问题，2005年7月乌鲁木齐河综合自动化系统工程（以下简称乌河综合自动化工程）全面开工建设。详细介绍了乌河综合自动化工程的7个子系统结构组成、功能，分析了自动化工程的初步效果，阐述了自动化工程的优点和缺点，提出了改进的建议。     

稀酸洗封闭净化流程设计

阐述稀酸洗封闭净化流程、运行中的存在问题及解决办法，并与水洗净化流程作一比较，为硫酸工艺设计提供一种新途径。     

超支化聚合物的研究进展及其在皮革工业中的应用前景

概述了超支化聚合物的发展、研究现状、结构性能及应用,分析了其在皮革工业中的应用前景,旨在通过对超支化聚合物相关内容的综述和介绍,为超支化聚合物在皮革工业中的应用起到抛砖引玉的作用     

武装直升机可靠性、维修性和保障性发展

介绍了国外武装直升机可靠性、维修性和保障性的发展历史与现状, 从中总结了一些规律性的结论。以AH-64A武装直升机为代表,全面地描述了RMS的实施贯彻过程,指出了武装直升机可靠性、维修性和保障性(RMS)将向着综合化、自动化、智能化和信息化方向发展。     

A Semantic Supervision Method for Abstractive Summarization

In recent years, many text summarization models based on pre-training methods have achieved very good results. However, in these text summarization models, semantic deviations are easy to occur between the original input representation and the representation that passed multi-layer encoder, which may result in inconsistencies between the generated summary and the source text content. The Bidirectional Encoder Representations from Transformers (BERT) improves the performance of many tasks in Natural Language Processing (NLP). Although BERT has a strong capability to encode context, it lacks the fine-grained semantic representation. To solve these two problems, we proposed a semantic supervision method based on Capsule Network. Firstly, we extracted the fine-grained semantic representation of the input and encoded result in BERT by Capsule Network. Secondly, we used the fine-grained semantic representation of the input to supervise the fine-grained semantic representation of the encoded result. Then we evaluated our model on a popular Chinese social media dataset (LCSTS), and the result showed that our model achieved higher ROUGE scores (including R-1, R-2), and our model outperformed baseline systems. Finally, we conducted a comparative study on the stability of the model, and the experimental results showed that our model was more stable.     

A complex network approach to text summarization

Automatic summarization of texts is now crucial for several information retrieval tasks owing to the huge amount of information available in digital media, which has increased the demand for simple, language-independent extractive summarization strategies. In this paper, we employ concepts and metrics of complex networks to select sentences for an extractive summary. The graph or network representing one piece of text consists of nodes corresponding to sentences, while edges connect sentences that share common meaningful nouns. Because various metrics could be used, we developed a set of 14 summarizers, generically referred to as CN-Summ, employing network concepts such as node degree, length of shortest paths, d-rings and k-cores. An additional summarizer was created which selects the highest ranked sentences in the 14 systems, as in a voting system. When applied to a corpus of Brazilian Portuguese texts, some CN-Summ versions performed better than summarizers that do not employ deep linguistic knowledge, with results comparable to state-of-the-art summarizers based on expensive linguistic resources. The use of complex networks to represent texts appears therefore as suitable for automatic summarization, consistent with the belief that the metrics of such networks may capture important text features.     

基于事件框架的移动摘要方法研究

本文提出了一种面向移动终端的文本摘要方法,该方法基于框架思想,将文本摘要生成过程分解为信息抽取和文本生成两个阶段。信息抽取阶段对原文进行词频统计,关键词句分析,并在此基础上利用规则抽取相应信息填充摘要框架。文本生成阶段利用框架编码协议对框架进行解析,并结合相关模板生成文本摘要。