环保型无氟化渣剂在攀钢炼钢中的应用

对攀钢集团西昌钢钒有限公司（以下简称西昌钢钒）铝脱氧钢精炼造渣机理进行了研究,根据理论分析精炼过程要求的"高碱度、高CaO活度、高熔化速度、低熔化温度"提出了一种新的无氟精炼化渣剂,主要成分为（/%:17 CaO,45 Al2O3,5 Na2O,4 MgO,5 SiO2）。该化渣剂已在西昌钢钒应用,在LF工序加入量控制在0.5～1.0 kg/t钢,新的无氟精炼化渣剂埋弧效果好,化渣速度快,M3A35等钢种3min左右即成渣,对于钢包罐侵蚀明显比使用萤石化渣好,渣线部位耐材无明显侵蚀。     

融雪剂对城市园林植物伤害机理的研究

通过现场调查和对土壤化验分析表明,撒施了融雪剂的雪水和树埯内土壤中的盐分和Cl-含量远远大于对照雪水和土壤,由此认为造成2003年北京城市大量行道树和灌木死亡的原因是由于融雪剂使用过多,使植株发生了严重盐害所致。同时研究表明,栾树、毛白杨、银杏和油松等行道树的衰弱或死亡还与道路两侧密实的土壤条件有关。     

基于多Agent的某型导弹智能诊断系统中网络模块的设计与实现

针对基于多Agent的某型导弹智能故障诊断系统中的Agent之间的通信问题,给出了该系统通信系统总体构成,应用IOCP线程管理方式和自定义通信协议数据包,能够实现实时监控状态下的多线程网络通信,最后给出了具体的功能函数定义和整个网络模块中Agent间的通信流程。     

T-ZnOw/TLCP抗静电复合材料的制备与性能研究

以热致液晶高分子(TLCP)为基体,四针状氧化锌晶须(T-ZnOw)为导电填料,用单螺杆挤出机制备抗静电性T-ZnOw/TLCP复合材料,分别探讨了偶联剂对T-ZnOw的影响;T-ZnOw用量对T-ZnOw/TLCP复合材料表面电阻率、热变形温度、力学性能的影响。结果表明,T-ZnOw经过偶联剂改性后,随着其用量的增加,复合材料表面电阻率显著下降,热变形温度、拉伸强度、冲击强度均呈现先增大后减小的趋势。     

Agent evaluation based on multi-source heterogeneous information table using TOPSIS

In agent evaluation, a specific role-playing may need more than one capabilities or the task execution process can be divided into several stages. The diverse perspectives to assess candidate agents are denoted as attributes, which is more practical than treating experts as attributes in many other works. In the evaluation table, the attribute values may come from different sources and the data types may not be the same. Therefore, we consider evaluation issues in a Multi-Source Heterogeneous Information System (MSHIS). Considering that grading, voting and marking are three common evaluation scenarios, linguistic variable, Intuitionistic Fuzzy Value (IFV) and real number are utilized to describe the corresponding evaluation results. To evaluate agents in MSHIS, a TOPSIS-based evaluation method is adopted in this work. In the proposed method, the range is utilized to nondimensionalize the distance between agents in each attribute. Then, a weighted Euclidean distance metric is adopted to measure the comprehensive distance. The relative closeness to the ideal agents reflects the agent’s capability on the concerned task. Finally, the illustrative example and comparative experiments are presented to illustrate the effectiveness of our method.     

Stable growing neural gas: A topology learning algorithm based on player tracking in video games

Characters in video games usually use a manually-defined topology of the environment to navigate. To evolve in an open, unknown and dynamic world, characters should not have pre-existing representations of their environment. In this paper, characters learn this representation by imitating human players. We here put forward a modified version of the growing neural gas model (GNG) called stable growing neural gas (SGNG). The algorithm is able to learn how to use the environment from one or more teachers (players) by representing it with a graph. Unlike GNG, SGNG learning is in-line, reflecting the dynamic nature of the environment. The evaluation of the quality of the learned representations are detailed.     

基于Agent的信任的情感劝说决策模型

基于智能体(Agent)的信任的情感劝说能更好地发挥Agent的各项人工智能优势。针对其中决策模型建立不够的现状,首先基于Agent的自身性格、情感衰减及外界刺激,运用大五性格、OCC情感模型及情感强度第一定律等,构建了相应的情感强度算法;其次考虑交易质量对信任的反馈,综合运用语言评价法、三角模糊数及将模糊数转换为具体分数(CFCS)算法,对Agent的交易质量进行模糊化和去模糊化处理,构建了相应的交易质量算法;再次对已有的信任更新因子进行改进后,构建了Agent的信任更新算法;最后在构建以上算法的基础上,采用交互式多准则决策(TODIM)法建立了基于Agent的信任的情感劝说决策模型,并采用熵权法对模型中的属性权重进行设定。为验证以上研究的合理性和有效性,设计了相应算例进行阐述,分析了不同参数取不同值得到的决策结果,并与相关研究进行了比较分析,得出了相应结论和管理启示,进一步归纳了不足之处和未来研究方向。     

Investigation on concentration characteristics of ozone micro-bubbles fixed in ice and ozone gas released from ice

Ice formed from water in which ozone gas is dissolved is promising for the cold storage of foods because of the ozone's sterilization and deodorization capabilities. However, effective dissolution of ozone gas in water and taking ozone gas into ice are not easy. Furthermore, the decomposition rate of the ozone itself is usually very fast, regardless of its phase. Thus, to effectively take ozone gas into ice, the authors have developed ice containing ozone micro-bubbles. In this paper, ice containing ozone micro-bubbles formed by adding surfactant was kept for a desired time at a desired constant temperature without melting of the ice. The concentration of ozone micro-bubbles fixed in ice and the ozone gas concentration released from ice by melting were measured to investigate the ozone decomposition rate due to fixation in ice and the characteristics of the released concentration. Furthermore, the influences of surfactant on both concentrations were examined.     

物联网中基于Multi-Agent的物间动态关系发现

物联网中存在大量异构关系的实体，其信息间的交互造成了物联网的内在矛盾。针对这一问题，提出将物联网中实体抽象化为对应的Agent，并以个体人为中心，利用本体的语义匹配及改进的物间动态关系计算方法，计算出针对个体人的物间动态关系；将原本异构的实体关系转化为Agent间基于动态关系紧密度排序的网络关系。经实验验证，该方法构建的关系网络可明显改善异构实体间交互的矛盾，而且相比原有类似方法，该方法解决问题的准确率和误差率均有改善，说明了该方法的准确性和可行性。     

A simulation testbed for analyzing trust and reputation mechanisms in unreliable online markets

Modern online markets are becoming extremely dynamic, indirectly dictating the need for (semi-) autonomous approaches for constant monitoring and immediate action in order to satisfy one’s needs/preferences. In such open and versatile environments, software agents may be considered as a suitable metaphor for dealing with the increasing complexity of the problem. Additionally, trust and reputation have been recognized as key issues in online markets and many researchers have, in different perspectives, surveyed the related notions, mechanisms and models. Within the context of this work we present an adaptable, multivariate agent testbed for the simulation of open online markets and the study of various factors affecting the quality of the service consumed. This testbed, which we call Euphemus, is highly parameterized and can be easily customized to suit a particular application domain. It allows for building various market scenarios and analyzing interesting properties of e-commerce environments from a trust perspective. The architecture of Euphemus is presented and a number of well-known trust and reputation models are built with Euphemus, in order to show how the testbed can be used to apply and adapt models. Extensive experimentation has been performed in order to show how models behave in unreliable online markets, results are discussed and interesting conclusions are drawn.