生物质转化的共性问题研究——生物质科学与工程学的建立与发展

生物质资源的高值转化是研究热点。由于现有的生物质利用技术存在的技术单一,缺乏系统性理论指导等问题,导致原料利用率低,经济效益差,难以实现工业化生产,迫切需要建立新的理论体系。通过深入分析生物质转化过程中的共性问题,在综合多学科知识的基础上,提出了生物质科学与工程学这一理念,从生物质原料工程学,生物质转化过程工程学和生物质产品工程学三方面对生物质利用技术进行了全面、系统的研究,为生物质类可再生资源的高值化利用提供了新的研究思路。     

黄金峡水利枢纽工程大型水泵机组选型设计及运行调节研究

引汉济渭工程黄金峡水利枢纽是陕西省境内一项重要的大型跨流域调水工程,泵站装机容量和设计流量均为目前国内甚至亚洲在建和已建泵站之最,且调水过程复杂、调水流量分布范围宽广。在分析黄金峡泵站调度原则及运行方式的基础上,综合比较目前国内外大型泵站机组设计制造水平、枢纽建筑物及机电设备投资等因素,详细论证了大型单级单吸离心式水泵机组台数和性能参数的确定方法及其影响因素,并给出了黄金峡泵站机组选型设计的最优方案,同时论证了采用变频调节的必要性及其效果。研究结果可为大型调水泵站机组的选型设计提供参考。     

基于发文内容的微博用户兴趣挖掘方法研究

本文针对微博用户兴趣属性缺失问题,提出一种基于发文内容分析的微博用户兴趣挖掘方法。利用基于短语的主题模型和自动构建的用户兴趣知识库,能够有效地从发文内容中挖掘出高质量的用户兴趣短语并标识其类别,从而实现对微博用户的兴趣挖掘。在SMP CUP 2016数据集上的实验结果表明,主题短语模型在困惑度和短语质量上取得的效果均优于传统的主题模型,用户兴趣挖掘的准确率和召回率最高可达到78%和82%。     

Managing knowledge on communication and information flow in global software projects

Communication is a key success factor of distributed software projects. Poor communication has been identified as a main obstacle to successful collaboration. Global projects are especially endangered by information gaps between collaborating sites. Different communication styles, technical equipment, and missing awareness of each other can cause severe problems. Knowledge about actual and desired channels, paths, and modes of communication is required for improving communication in a globally distributed project. However, many project participants know little about communication and information flow in their projects. In this contribution, we focus on knowledge about communication and information flow. It is acquired by modelling on‐going and desired flows of information, including documented and non‐documented channels of information flow. We analyzed a distributed software project from the information flow perspective. Based on the findings, we developed specific techniques to improve information flow in distributed software development according to the FLOW Method. In a second distributed project, we evaluated one of the techniques. We found the FLOW mapping technique to be suitable for effectively spreading knowledge about communication and information flow in global software projects.     

催化精馏合成异丙苯过程催化剂装填结构研究

为考察不同催化剂装填结构对催化精馏合成异丙苯过程的影响 ,在热态反应器中进行苯烃化催化精馏合成异丙苯的研究。反应器直径为 3 0mm ,高 2 0 0 0mm ,所用催化剂为 β改性沸石分子筛。操作压力0 .7MPa ,温度 43 0— 480K ,苯质量空速 4— 6h- 1 ,苯烯摩尔比 1.1— 2 .2 ,回流比 9— 2 0。催化剂装填结构由不锈钢填料与催化剂颗粒组成 ,三种装填结构的空隙率分别为 85 .1% ,81.6%和 79.4%。结果表明 ,对于异丙苯合成体系 ,装填结构对催化精馏的总体效果起决定性影响。在催化剂装填总量不变的前提下 ,异丙苯的选择性与丙烯的转化率均随催化剂装填结构空隙率的提高而提高。在优化条件下 ,异丙苯的选择性达97% ,丙烯转化率接近 10 0 %。催化剂装填结构对异丙苯选择性的影响比对丙烯转化率的影响更显著     

Integration by communication: knowledge exchange in global outsourcing of product software development

Global outsourcing is a growing trend among independent software vendors. In these projects like other distributed work, distances have negative effects on communication and coordination, directly impacting performance. We present a normative model designed to address this issue by improving communication and knowledge exchange. The model consists of six distinct practices and a tool blueprint, each coming with practical guidelines. It is based in part on two case studies of Dutch software vendors who have successfully outsourced part of their activities to an Eastern European outsourcing vendor, and validated by a panel of six experts from industry and the scientific community. It is concluded that knowledge exchange in global software outsourcing is a by‐product of efforts to enhance communication and coordination, rather than specific technical solutions. By committing to sharing knowledge, emphasizing transparency and integrating the outsourcing team into their organizations, customers from the product software business can realize the benefits of global outsourcing.     

Computational Problem Solving in Spatial Substrates -- A Cognitive Systems Engineering Approach

The ability to perform spatial tasks is crucial for everyday life and of great importance to cognitive agents such as humans, animals, and autonomous robots. A common artificial intelligence approach to accomplish spatial tasks is to represent spatial configurations and tasks in form of detailed knowledge about various aspects of space and time. Suitable algorithms then use the representations to compute solutions to spatial problems. In comparison, natural embodied and situated agents often solve spatial tasks without detailed knowledge about geometric, topological, or mechanical laws; they directly relate actions to effects that are due to spatio-temporal affordances in their bodies and environments. Accordingly, we propose a paradigm that makes the spatio-temporal substrate an integral part of the engine that drives spatial problem solving. We argue that spatial and temporal structures in body and environment can substantially support (and even replace) reasoning effort in computational processes: physical manipulation and perception in spatial environments substitute formal computation. While the approach is well known – for example, we employ diagrams as spatial substrate for geometric problem solving and maps for wayfinding – the underlying principle has not been systematically investigated or formally analyzed as a paradigm of cognitive processing. Topology, distance, and orientation constraints are all integrated and interdependent in truly 2- or 3-dimensional space. Exploiting this fact may not only help overcome the need for acquiring detailed knowledge about the interrelationships between different aspects of space; it also can point to a way of avoiding exploding computational complexity that occurs when we deal with these aspects of space in complex real-world scenarios. Our approach employs affordance-based object-level problem solving to complement knowledge-level formal approaches. We will assess strengths and weaknesses of the new cognitive systems paradigm.     

Mechanisms of hydrocarbon conversion reactions on heterogeneous catalysts: analogies with organometallic chemistry

Catalysis is central to most industrial processes for chemical manufacturing. As catalytic processes have become more complex and more demanding, selectivity has become the central issue in their design. Selectivity is defined by the relative rates of competing reaction pathways available to crucial intermediates, and can be controlled by subtle changes in the nature of the catalyst, the reactants, and/or the reaction conditions. In order to be able to do this in a systematic manner, a good understanding of the catalytic reaction mechanisms is needed. Here a connection is drawn between the key elementary steps comprising hydrocarbon conversion reactions on surfaces and those known to occur on discrete organometallic complexes. This way, the hydrogenation, dehydrogenation, hydrogenolysis, chain growth, and isomerization reactions typical in heterogeneous catalysis are redefined in terms of hydride elimination, oxidative addition, reductive elimination, migratory insertion, and 1, 2-shift elementary steps, among others. It is suggested that the knowledge already available from organometallic chemistry can be used to further advance the understanding of the surface science involved in heterogeneous catalysis. Thanks to the commonality of the chemistry involved, a better synergy could also be established between homogeneous and heterogeneous catalytic development. These ideas are discussed in this article in a critical and personal way.*Invited contribution to the special volume entitled The Interface between Heterogeneous and Homogeneous Catalysis, stemming from contributions at the recent International Symposium on Relations between Heterogeneous and Homogeneous Catalysis, and dedicated to the memory of Robert L. Burwell.     

Perception of own and robot engagement in human–robot interactions and their dependence on robotics knowledge

Communication between socially assistive robots and humans might be facilitated by intuitively understandable mechanisms. To investigate the effects of some key nonverbal gestures on a human’s own engagement and robot engagement experienced by humans, participants read a series of instructions to a robot that responded with nods, blinks, changes in gaze direction, or a combination of these. Unbeknown to the participants, the robot had no form of speech processing or gesture recognition, but simply measured speech volume levels, responding with gestures whenever a lull in sound was detected. As measured by visual analogue scales, engagement of participants was not differentially affected by the different responses of the robot. However, their perception of the robot’s engagement in the task, its likability and its understanding of the instructions depended on the gesture presented, with nodding being the most effective response. Participants who self-reported greater robotics knowledge reported higher overall engagement and greater success at developing a relationship with the robot. However, self-reported robotics knowledge did not differentially affect the impact of robot gestures. This suggests that greater familiarity with robotics may help to maximise positive experiences for humans involved in human–robot interactions without affecting the impact of the type of signal sent by the robot.     

智能化结构分析建模方法

建立正确的模型是进行机械结构分析的关键技术之一。提出了一种基于知识的结构分析建模方法,给出了基于知识结构分析建模方法的总体结构,讨论了知识的获取、分类与表达,提出了推理机制以及智能求解策略,提高了结构有限元分析建模方法的实用性和有效性。最后用实例说明了应用效果。