QD-Janus: A sequential implementation of Janus in Prolog

Janus is a language designed for distributed constraint programming. This paper describes QD-Janus, a sequential implementation of Janus in Prolog. The compiler uses a number of novel analyses and optimizations to improve the performance of the system. The choice of Prolog as the target language for a compiler, although unusual, is motivated by the following: (i) the semantic gap between Janus and Prolog is much smaller than that between Janus and, say, C or machine language—this simplifies the compilation process significantly, and makes it possible to develop a system with reasonable performance fairly quickly; (ii) recent progress in Prolog implementation techniques, and the development of Prolog systems whose speeds are comparable to those of imperative languages, indicates that the translation to Prolog need not entail a significant performance loss compared to native code compilers; and (iii) compilation to Prolog can benefit immediately from a significant body of work on, and implementations of, parallel Prolog systems. Our experience indicates that translation of logic programming languages to Prolog, accompanied by the development of good program analysis and optimization tools, is an effective way to quickly develop flexible and portable implementations with good performance and low cost.     

Artificial intelligence and symbols

The introduction of massive parallelism and the renewed interest in neural networks gives a new need to evaluate the relationship of symbolic processing and artificial intelligence. The physical symbol hypothesis has encountered many difficulties coping with human concepts and common sense. Expert systems are showing more promise for the early stages of learning than for real expertise. There is a need to evaluate more fully the inherent limitations of symbol systems and the potential for programming compared with training. This can give more realistic goals for symbolic systems, particularly those based on logical foundations.     

Integration of knowledge-based systems with data processing

Transaction Oriented Prolog-Online Environment is a multi-user, mainframe implementation of the logic programming language Prolog, specially designed and developed for the data processing environment. This article describes the background, functionality, implementation and use of TOP-ONE, stressing that applications of knowledge-based systems technology to data processing environments will achieve full success only when existing systems and existing conventional data are incorporated within the applications.     

MetateM: An introduction

In this paper a methodology for the use of temporal logic as an executable imperative language is introduced. The approach, which provides a concrete framework, calledMetateM, for executing temporal formulae, is motivated and illustrated through examples. In addition, this introduction provides references to further, more detailed, work relating to theMetateM approach to executable logics.     

主动推送模式下的情报需求预测模型

针对主动推送模式下的情报需求预测问题,提出了基于案例推理的解决方案。设计了进行情报需求预测案例分析的工作流程,建立了案例属性描述模型;应用最近邻法进行案例的相似度评价,并通过信息增益的计算确定每个属性的权值,获得相似案例(集);提出了方案调整和推理策略。     

串联谐振耐压试验仪的设计与仿真

针对XLPE电力电缆耐压测试成本高、操作复杂等问题,本文中设计了一种变频串联谐振耐压试验装置。利用串联谐振电路的升压原理,构建了硬件电路,通过仿真对选择谐振点等问题进行了探讨。为了改进普通串联谐振耐压测试装置寻找谐振点慢、精度低的缺点,提出了一种解决方案。仿真结果表明,该方法能精确地确定谐振点。装置输出波形可靠性好,谐波分量少,具有良好的性能。     

单周期控制Boost—PFC基于Saber的设计与仿真

单周期控制策略简单可靠,动态响应速度快,能很好地抑制输入电压扰动和负载突变。本文阐述了单周期控制Boost—PFC的工作原理,对单周期控制Boost—PFC进行了基于Saber软件的CAD设计和仿真。仿真结果表明,单周期控制适用干Boost变换器,能够实现功率因数校正。     

一种分析时序逻辑电路的补充方法

介绍一种分析时序逻辑电路的补充方法,并应用于教学实践中。其特点是原理简单、易于理解、直观方便,相对于传统的分析方法,避免了对次状态方程的分析处理计算,有时比传统方法简便、快捷。通过两个示例展示其优越性。     

背包问题最优解的结构

讨论背包问题的最优解,引入背包问题的阶的概念,并对背包问题的阶作出深入的讨论,在此基础上得到背包问题的最优解的一般形式。