基于统计抽词和格律的全宋词切分语料库建立

全宋词切分语料库的建立是计算机研究宋词的基础。本文对宋词中“词”的界定提出了自己的看法,并在综合考虑统计抽词方法和基于诗词格律切分方法各自优点的基础上,提出建立全宋词切分语料库的新方法。我们首先通过统计抽词来抽取结合程度较强的二字词,并结合相关资源建立词表;在此基础上,结合宋词的格律特点按照一定的规则来对全宋词进行了切分。实验证明,本文中的方法具有较好的效果。国家自然科学基金资助项目(60373080

Effect of Flue-gas Cleaning Devices on Mercury Emission From Coal-fired Boiler

为研究燃煤锅炉烟气净化设施对汞排放特性的影响,采用Ontario-Hydro方法,对设有催化脱硝、静电除尘、海水脱硫的300MW燃煤锅炉排放烟气中汞的含量与形态进行分析,同时测定锅炉的煤、底渣、飞灰等固体样品以及脱硫塔前后、曝气之后海水样品中的汞含量。实验结果为:烟气中的气态汞占总汞的79.1%以上,脱硝催化剂对汞的价态具有强烈的转化作用,烟气中83.4%的气态Hg0被氧化成气态Hg2+;静电除尘对颗粒态汞的去除率几乎达到100%;在脱硫塔中,海水对烟气中汞的洗脱率高达73.6%,曝气后排放前的海水中含汞量是新鲜海水的5.5倍。研究表明锅炉烟气净化设施对汞的排放特性有着重要的影响。In order to study the effect of flue-gas cleaning devices on mercury emission from coal-fired boiler, Ontario-Hydro method had been applied to determine the mercury concentration and speciation in the flue-gas emitted from a 300MW coal-fired boiler, which was equipped with various pollution control devices, including selective catalyst reduction (SCR) De-NOx system, electrostatic precipitator (ESP), and flue-gas seawater De-SO2 system (FGD). Mercury concentration in raw coal, bottom ash and fly ash of the boiler, seawater at the inlet and outlet of SO2 absorption reactor and the drainage of aeration sink, were also analyzed. The results indicate that the percentage of gaseous mercury in total mercury discharged is more than 79.1%. De-NOx catalyst strongly affects the mercury speciation transformation, showing a conversion rate of 83.4% for Hg0 to Hg2+. The removal efficiency of particulate mercury by ESP is close to 100%. With seawater FGD, the removal efficiency of mercury is as high as 73.6%. The mercury concentration in the seawater of drainage from aeration sink is 5.5 times higher than that in fresh seawater. The study shows that the flue-gas cleaning devices in coal-fired power plant play an important role on mercury emission characterization

Plenty is Plague: Fine-Grained Learning for Visual Question Answering

纪荣嵘教授团队的论文提出了一种基于强化学习的细粒度学习策略FG-A1C，旨在通过分析视觉问答任务中的样本多样性及标签的冗余性问题来针对性地挑选训练样本以提高模型的训练效率及减少标记支出。 该论文由厦门大学媒体分析与计算实验室的周奕毅博士后助理研究员、纪荣嵘教授（通信作者）、孙晓帅副教授、苏劲松副教授，以及西安交通大学孟德宇教授、清华大学高跃副教授和澳大利亚阿德莱德大学沈春华教授等合作完成。Visual Question Answering (VQA) has attracted extensive research focus recently. Along with the ever-increasing data scale and model complexity, the enormous training cost has become an emerging challenge for VQA. In this paper, we show such a massive training cost is indeed plague. In contrast, a fine-grained design of the learning paradigm can be extremely beneficial in terms of both training efficiency and model accuracy. In particular, we argue that there exist two essential and unexplored issues in the existing VQA training paradigm that randomly samples data in each epoch, namely, the "difficulty diversity" and the "label redundancy". Concretely, "difficulty diversity" refers to the varying difficulty levels of different question types, while "label redundancy" refers to the redundant and noisy labels contained in individual question type. To tackle these two issues, in this paper we propose a fine-grained VQA learning paradigm with an actor-critic based learning agent, termed FG-A1C. Instead of using all training data from scratch, FG-A1C includes a learning agent that adaptively and intelligently schedules the most difficult question types in each training epoch. Subsequently, two curriculum learning based schemes are further designed to identify the most useful data to be learned within each inidividual question type. We conduct extensive experiments on the VQA2.0 and VQA-CP v2 datasets, which demonstrate the significant benefits of our approach. For instance, on VQA-CP v2, with less than 75% of the training data, our learning paradigms can help the model achieves better performance than using the whole dataset. Meanwhile, we also shows the effectivenesss of our method in guiding data labeling. Finally, the proposed paradigm can be seamlessly integrated with any cutting-edge VQA models, without modifying their structures.This work is supported by the National Key R&D Program (No.2017YFC0113000, and No.2016YFB1001503), Nature Sci- ence Foundation of China (No.U1705262, No.61772443, and No.61572410), Post Doctoral Innovative Talent Support Pro-gram under Grant BX201600094, China Post-Doctoral Sci- ence Foundation under Grant 2017M612134, Scientific Re-search Project of National Language Committee of China (Grant No. YB135-49), and Nature Science Foundation of Fu-jian Province, China (No. 2017J01125 and No. 2018J01106). 本项研究得到了厦门大学“人工智能分析引擎”双一流重大专项的支持、国家重点研发专项和国家自然科学基金海峡基金等项目的支持

新疆塔里木灌区水盐问题研究

土壤盐碱化和次生盐渍化是威胁塔里木灌区农业生产的主要因素之一。作者主要以水田向水盐平衡为指导分析了塔里木灌区当前水土资源利用方式下的灌区田间尺度的盐分动态、灌区尺度的盐碱化趋势及影响因素以及农田排水的解决对策,估算了地下水临界深度及灌排比,初步探讨了当前节水农业条件下灌区所可能存在的主要问题。文中最后强调:理论上应加强对灌区作物需水研究及水盐运移与聚集规律,特别是节水条件下的根区土壤盐分平衡问题研究;实践中通过完善灌排管理、提高常规灌溉技术的灌溉效率,逐步进行种植业的结构调整,是塔里木灌区灌溉农业持续发展的基础

An Improved Evolutionary Algorithm for Traveling Salesman Problem Based on Inver-Over Operator

使用逆转算子求解TSP的演化算法具有很强全局搜索能力,在求解TSP问题中显示了巨大的优势。但是,该算法同样存在执行效率低、最终得到的最优个体整体质量不高等缺陷。在对算法和TSP问题进行分析的基础上,对算法进行三方面的改进:就近选择;动态变异概率;基于较优个体的贪婪搜索。实验结果表明:经过改进的算法提高了执行效率,能够改善算法得到的最优个体的整体质量。The evolutionary algorithm using inver-over operator for the traveling salesman problem(TSP) has great ascendancy,because its ability in global searching for optimal individual is powerful.However,it has the some limitations: low executive efficiency and the dissatisfactory average individuals obtained by algorithm.To avoid these limitations,improves the algorithm mentioned above in three aspects: close-by visit method,dynamic mutation probability and greedy search based on preferable individuals.A desirable result is obtained.It is showed by the experiment that the algorithm can be executed with high efficiency and the average quality of the optimal individual of the algorithm is improved

The Impact of Phubbing in Digital Back-feeding on Elderly Parents'Mental Health

老年人是抑郁和焦虑的高发群体,良好的数字融入是提升心理健康的重要途径.基于家庭的数字反哺是老年人数字融入的内生有效力量.然而,数字反哺的进程常常受到子女行为影响.本研究关注老年人感知的子女低头行为,即子女与父母互动中因使用手机对父母造成的&quot;情感冷落&quot;如何影响老年人接受数字反哺时的心理预期以及情绪状态,进而影响心理健康.研究发现,老年人感知的子女低头行为会增加老年人的数字反哺障碍,诱发消极情绪,增加老年人的抑郁和焦虑倾向;但感知的子女低头行为对老年人的数字反哺效能感则无显著影响.本研究关注数字反哺的情感面向,刻画深度媒介化社会中老年人家庭传播实践的心理动态,揭示了阻碍数字反哺的因素与影响机制,力求为家庭传播的干预提供准确依据.</p