Response-adaptive trial designs with accelerated Thompson sampling

In a clinical trial, sometimes it is desirable to allocate as many patients as possible to the best treatment, in particular, when a trial for a rare disease may contain a considerable portion of the whole target population. The Gittins index rule is a powerful tool for sequentially allocating patients to the best treatment based on the responses of patients already treated. However, its application in clinical trials is limited due to technical complexity and lack of randomness. Thompson sampling is an appealing approach, since it makes a compromise between optimal treatment allocation and randomness with some desirable optimal properties in the machine learning context. However, in clinical trial settings, multiple simulation studies have shown disappointing results with Thompson samplers. We consider how to improve short-run performance of Thompson sampling and propose a novel acceleration approach. This approach can also be applied to situations when patients can only be allocated by batch and is very easy to implement without using complex algorithms. A simulation study showed that this approach could improve the performance of Thompson sampling in terms of average total response rate. An application to a redesign of a preference trial to maximize patient's satisfaction is also presented.     

赛珍珠《大地》叙事空间的置遣谫论

赛珍珠的《大地》虽然是用传统叙事写法创作的小说,但仍带有明显的叙事空间化的倾向,体现了时空维度的统一。小说以王龙一家所居村庄为基点空间,同时又设置了附近的城镇和南方大城市两个外缘空间。三大空间都具有表征人物性格、助推情节发展和突显主题思想等多种功能。三大空间都蕴含着地理、社会、文化、心理等方面因素,都由场域、场景和场面三个层次构成,并都表现出实在性、主体性和能动性三大特征。深厚的生活积累和谙熟中国小说写法是作者得以充分发挥空间叙事的长处并圆满完成故事讲述宗旨的决定性前提。     

社区应急疏散动态协作调度优化研究

针对灾民数量和路网通行时间的动态性以及灾民疏散反应系数的随机性，本文提出了社区应急疏散协作调度优化流程，并以疏散灾民数量最大化和疏散成本最小化为目标，构建了社区应急疏散多种运输方式协作调度优化模型，并给出了求解该模型的改进多目标遗传算法。然后，论文使用Tansmodeler模拟社区应急疏散协作调度优化过程，加载疏散灾民动态需求和历史出行时间表，并对模型和算法进行验证。结果表明，该模型和算法可以在有效刻画疏散灾民数量和路网通行时间的基础上，为不同时刻的交通工具配置及疏散路径选取提供决策。     

On-Line Scheduling of Two-Machine Open Shops Where Jobs Arrive Over Time

We investigate the problem of on-line scheduling two-machine open shops with the objective of minimizing the makespan.Jobs arrive independently over time, and the existence of a job is not known until its arrival. In the clairvoyant on-line model, the processing requirement of every job becomes fully known at the arrival of the job, while inthe non-clairvoyant on-line model, this processing requirement is notknown until the job is processed and completed.In both models, scheduling of a job is irrevocable.We study the two-machine open shop problem for both models in the preemptive and in the non-preemptive version. For each of the four variants, we provide an algorithm that is best possible with respect to the worst-case performance. In the clairvoyant on-line model, the best worst-case performance ratios are 5/4 (preemptive) and 3/2 (non-preemptive), and in the non-clairvoyant on-line model, they are 3/2 (preemptive and non-preemptive).     

桶装水灌装机优化设计

针对现有桶装水灌装生产线中灌装机产能较低、产品适应能力差的缺点,提出了能够适用于19升、17升、11升等多种桶型的高速柔性化灌装机的设计方案。灌装机的灌装头采用气动比例调节阀搭配传感器进行闭环控制,使得灌装液位精确,减少液体飞溅;进瓶装置采用星轮拨爪和由伺服电机驱动的链条传动装置联动的方式,实现水桶的精准拉距,实现多种瓶型快速切换的功能;瓶盖输送机构,结合盖子杀菌柜,实现在线杀菌功能,安全可靠。应用结果表明文章的设计能改善原有桶装水灌装机柔性差、速度慢、可靠性低的现状。优化设计的桶装水灌装机提高了生产效率,降低成本。     

Pareto mimic algorithm: An approach to the team orienteering problem

The team orienteering problem is an important variant of the vehicle routing problem. In this paper, a new algorithm, called Pareto mimic algorithm, is proposed to deal with it. This algorithm maintains a population of incumbent solutions which are updated using Pareto dominance. It uses a new operator, called mimic operator, to generate a new solution by imitating an incumbent solution. Furthermore, to improve the quality of a solution, it employs an operator, called swallow operator which attempts to swallow (or insert) an infeasible node and then repair the resulting infeasible solution. A comparative study supports the effectiveness of the proposed algorithm, especially, our algorithm can quickly find new better results for several large-scale instances. We also demonstrate that Pareto mimic algorithm can be generalized to solve other routing problems, e.g., the capacitated vehicle routing problem.     

附着与隧通——心智的工作模式

深度学习框架加速了人工智能技术的发展,越来越多的人工智能系统在专业领域超越人类,但沿此路径能否指引机器模拟出类人智能仍然没有定论。强计算主义的观点主张意识和智能可以被物理还原,甚至可以忽略意识。哥德尔等学者则倾向于机器无法模拟或超越人类。文章提出认知坎陷（意识片段）的“附着”与“隧通”这一对范畴,从新的视角探讨心智的工作模式。认知坎陷具有超越时空和流变的特性,在某时某地某景可以“附着”在某个具体对象之上。认知坎陷之间可以通过“隧通”链接成一个网络。“自我”作为最原初和最重要的认知坎陷,是人类意识与智能的发端。智能的作用之一是在情景改变时将“自我”“附着”到更合适的对象上。     

基于人工神经网络的在线设备状态监测系统的研究(英文)

研究了基于人工神经网络在线设备状态监测系统,简要介绍了人工神经网络的基础理论,描述了基于人工神经网络在线设备状态监测系的结构和工作过程,给出该系统对卷烟机MK9-5的状态监测和故障诊断的结果。实验结果表明,将多层前馈人工种经网络用于设备在线状态监测具有较好的效果,并可对设备故障进行可靠诊断。     

机器翻译中的多义问题探析

机器翻译(MachineTranslation)是自然语言处理中的一个研究分支,其发展应建立在完善的语言学研究的基础上。词义学层面中词性的多样性、词义的多义性和格的多义性,语用学层面中的指示多义性及会话含义多义性给机器翻译造成了障碍,而加强机译系统中的词典研究,重视机译系统中上下文的处理,设计强有力的机译文法体系则是解决这些问题的有效途径。     

汉英平行语料库双语语义对应空位研究

双语词语语义对应空位现象是英汉互译的常见障碍。在建立英汉平行语料库的过程中,这也是无法回避的问题。本文拟总结目前已建成的一些语料库处理这一问题的习惯方式,并在此基础上借鉴机器翻译研究领域的理论成果,试图做出更加细致的分析并提出更加可行的解决方案。