社交网络中基于信任评估的推荐控制模型

针对社交网络中无法有效管理陌生推荐安全性难题,提出了一种基于信任的评估推荐控制模型(TRCM).该模型描述了社交网络推荐中个体角色、推荐路径、可信任值、控制规则等方面内容.模型结合社交网络个体之间取信度、信誉度评估方法,分别计算串路型、并路型和复合型3类推荐信任度,并给出了客观偏移度和信心指数评估.同时,TRCM定义了一组信任控制规则以管理社交网络中的推荐行为.实验表明,该方法是有效可行的.     

均衡约束数学规划问题的一种新的约束规格

本文研究了均衡约束数学规划(MPEC)问题.利用其弱稳定点,获得了一种新的约束规格–MPEC的伪正规约束规格.用一种简单的方式,证明了该约束规格是介于MPEC-MFCQ(即MPEC,Mangasarian-Fromowitz约束规格)与MPEC-ACQ(即MPEC,Abadie约束规格)之间的约束规格,因此该约束规格也可以导出MPEC问题的M-稳定点.最后通过两个例子,说明了该约束规格与MPEC-MFCQ以及与MPEC-ACQ之间是严格的强弱关系.     

Mastercam软件后处理程序的开发研究

介绍了如何根据机床不同的控制系统对后处理程序进行开发,从而扩大了数控软件的功能．     

P-stable models of strong kernel programs

The research community has long recognized the study of non-monotonic reasoning (NMR) as a promising approach to model features of commonsense reasoning. We study one of the semantics that are useful to formalize NMR, called the p-stable semantics. We introduce three different formats for normal programs: negative normal programs, restricted negative normal programs and strong kernel programs. These forms help to simplify the search of p-stable models of the original program. One of the main results of this paper indicates that the p-stable semantics for strong kernel programs is the same as the stable semantics. This way, all the applications based on stable semantics for those kernel programs (defined in [S. Costantini, A. Provetti, Normal forms for answer set programming, J. Theory Pract. Log. Program. 5 (2005) 747-760]) that are strong kernel programs can also be based on the p-stable semantics.