基于市场机制的移动Agent系统资源管理

分析了移动Agent的运行机制：移动Agent运行时要消耗所在主机的计算机资源，恶意的移动Agent可以通过大量占用主机资源，引发服务拒绝攻击，因此主机资源的管理是移动Agent系统设计的重要环节。讨论了使用货币的基于市场机制的资源管理策略及主机资源的静态和动态定价策略，同时对实现进行了分析。     

计算机图解法确定掩蔽剂存在下微溶物沉淀的pH值

采用计算机图解法，以副反应系数为主变数，应用Excel电子表格和Origin作图程序进行计算、作图，可以极为简便地确定在掩蔽剂存在下，微溶物开始沉淀时和完全沉淀时的pH值，图形直观明了，具有确定的物理意义。     

浅谈SNMP与NMCA

介绍了传统的基于C/S的SNMP网络管理方案,阐述了Mob ile Agent技术优势,针对SNMP的不足提出了一种基于MA环境下的网络管理体系结构NMCA,并详细论述了该体系结构的实现机制.     

快速渗透剂T的制备新工艺（Ⅰ）相转移催化剂的选择

该文报道了由马来酸酐制备琥珀酸二异辛酯磺酸钠过程中产生的产物和副产物作磺化反应的催化剂的研究。对以来酸单酯钠盐，马来酸双酯的磺酸钠盐和磺化废水的相转移催化作用进行了研究对比。     

钢渣-钒钛矿渣基坑回填料的制备及机理

为了推动钢铁冶金废弃物的综合利用,以钢渣、钒钛矿渣为原料替代水泥制备了全固废预拌固化剂,再与黏土制成基坑回填料,采用力学性能测试法、X射线衍射(X-ray diffraction, XRD)、扫描电镜(scanning electronic microscopy, SEM)和能谱分析(energy dispersive spectrometry, EDS)等测试手段,研究了钢渣细度、钢渣掺量及固化剂掺入比对基坑回填料性能的影响,并测试预拌固化剂的稳定性及水化机理。结果表明：当钢渣比表面积为457 m²/kg,料浆浓度(质量分数)为80%,固化剂掺入比(质量分数)为20%,固化剂配比(质量比)为钢渣∶脱硫石膏∶钒钛矿渣=44∶10∶46时,用其制备的基坑回填料力学性能较好,此时固化剂净浆流动度为136 mm且安定性合格,稳定性优于P·O 42.5普通硅酸盐水泥;在固化剂掺入比为7%～25%,掺入占胶结剂总量0.4%PC型聚羧酸型高效减水剂(polycarboxylic acid, PC),基坑回填料28 d抗压强度均大于0.4MPa,最大为4.7 MPa,回填料坍落...     

Linux中基于Agent的进程迁移

探讨在Linux操作系统中基于代理的进程迁移方法,包括代理的组织、代理的通讯方式、迁移进程信息的获取及进程迁移后未完成报文和打开文件的处理等.     

工业废酸与硫酸渣制备三氯化铁的试验研究

介绍了利用工业废盐酸与硫酸渣制备三氯化铁的工艺,试验结果表明,在最佳工艺条件下,即液固比3∶1,浸出时间60min,矿物粒度0.18mm时,可使铁的浸出率达到79.67%。实验证明该工艺具有试验设备简易,工艺流程短,技术可靠的优点。     

减水剂对掺电石渣水泥砂浆强度影响的研究及配方确定

采用正交试验法探讨掺入减水剂后各因素对掺电石渣的水泥砂浆强度的影响,确定水泥砂浆强度性能较佳的配方并分析其微观结构.结果表明:掺入减水剂后,对掺电石渣的水泥胶砂试样早期抗压强度的影响从大到小的次序分别为胶砂比、水灰比、电石渣掺量、减水剂掺量、减水剂品种、搅拌时间、减水剂的掺入方式.正交试验法确定的水泥胶砂试样较佳的配方为,电石渣掺量为5%;减水剂为J2,采用后掺方式,其掺量为0.5%;水灰比为0.377;胶砂比为1∶1.5;搅拌时间为9 min.     

Learning Pet -- Intelligent Agents for WBE

An intelligent agent is any program that can be considered by the user to be acting as an assistant or helper, rather than as a tool in the manner of a conventional direct-manipulation interface. An agent should as well display some, but perhaps not all, of the characteristics that are associated with human intelligence: learning, inference, adaptability,independence, creativity, etc.. In order to make webbased education (WBE) more vividly and instructionally with learner's independence at the same time, the intelligent agent can act as a learning pet, which is affiliated with learner's score or grades and will grow up with learner's achievement. And during the course of study, the learning pet can provides any information required by the learner, gives hints if necessary when the learner doing his/her assignment, offers instructional guide for further study etc..     

Generalized Reactive Manufacturing System

Generalized reactive manufacturing system named GRMS is introduced. GRMS is a human-centered system based on Multi-agent. Its management and control organization is made up of three types of agents named device agent, task agent and shop-floor agent. GRMS adopts a top-down and bottom-up competition and cooperation strategy based on the dynamic sifter and funnel . To constrain the behavior of agents, a reward and penalty policy is introduced into the system and the closed-loop adjustment of GRMS is realized through such policy. Agents for the same task should be cooperated with each other and agents for different tasks should compete for survival in the dynamic changing environment. A distributed-hierarchical architecture with three levels of master-slave relationships among agents are proposed. Self-propelled process planning is also discussed. In order to evaluate GRMS, a time-driven simulation system-GRMOSS is developed to check the physical consistency of GRMS.