仿真在战术互联网效能评估中的应用

效能评估是战术互联网建设的重要内容,仿真是效能评估的关键技术.在分析战术互联网效能评估方法的基础上提出了基于HLA的战术互联网分布式仿真系统体系结构,基于战术互联网战场环境的特点建立了网络场景模型,并从对路由协议性能的影响方面与目前常用网络仿真环境模型进行了比较,仿真结果说明不同的网络场景模型将对战术互联网性能仿真产生较大的影响从而影响效能评估结果.文章所建立的战术互联网仿真系统体系结构和网络场景模型可以对战术互联网性能仿真和效能评估提供一定参考.     

Prolog/Rex-a way to extend Prolog for better knowledgerepresentation

Prolog/Rex represents a powerful amalgamation of the latest techniques for knowledge representation and processing, rich in semantic features that ease the difficult task of encoding heterogeneous knowledge of real-world applications. The Prolog/Rex concept mechanism lets a user represent domain entities in terms of their structural and behavioral properties, including multiple inheritance, arbitrary user-defined relations among entities, annotated values (demons), incomplete knowledge, etc. A flexible rule language helps the knowledge engineer capture human expertise and provide flexible control of the reasoning process. Additional Prolog/Rex strength that cannot be found in any other hybrid language made on top of Prolog is language level support for keeping many potentially contradictory solutions to a problem, allowing possible solutions and their implications to be automatically generated and completely explored before they are committed. The same mechanism is used to model time-states, which are useful in planning and scheduling applications of Prolog/Rex     

Improving the Decompilation of Java Bytecode to Prolog by Partial Evaluation

The interpretative approach to compilation allows compiling programs by partially evaluating an interpreter w.r.t. a source program. This approach, though very attractive in principle, has not been widely applied in practice mainly because of the difficulty in finding a partial evaluation strategy which always obtain “quality” compiled programs. In spite of this, in recent work we have performed a proof of concept of that, at least for some examples, this approach can be applied to decompile Java bytecode into Prolog. This allows applying existing advanced tools for analysis of logic programs in order to verify Java bytecode. However, successful partial evaluation of an interpreter for (a realistic subset of) Java bytecode is a rather challenging problem. The aim of this work is to improve the performance of the decompilation process above in two respects. First, we would like to obtain quality decompiled programs, i.e., simple and small. We refer to this as the effectiveness of the decompilation. Second, we would like the decompilation process to be as efficient as possible, both in terms of time and memory usage, in order to scale up in practice. We refer to this as the efficiency of the decompilation. With this aim, we propose several techniques for improving the partial evaluation strategy. We argue that our experimental results show that we are able to improve significantly the efficiency and effectiveness of the decompilation process.     

Oracle Semantics for Prolog

This paper proposes to specify semantic definitions for logic programming languages such as Prolog in terms of an oracle which specifies the control strategy and identifies which clauses are to be applied to resolve a given goal. The approach is quite general. It can be applied to Prolog to specify both operational and declarative semantics as well as other logic programming languages. Previous semantic definitions for Prolog typically encode the sequential depth-first search of the language into various mathematical frameworks. Such semantics mimic a Prolog interpreter in the sense that following the "leftmost" infinite path in the computation tree excludes computation to the right of this path from being considered by the semantics. The basic idea in this paper is to abstract away from the sequential control of Prolog and to provide a declarative characterization of the clauses to apply to a given goal. The decision whether or not to apply a clause is viewed as a query to an oracle which is specified from within the semantics and reasoned about from outside. This approach results in simple and concise semantic definitions which are more useful for arguing the correctness of program transformations and providing the basis for abstract interpretations than previous proposals.     

Difference-list transformation for Prolog

Difference-lists are terms that represent lists. The use of difference-lists can speed up most list-processing programs considerably. Prolog programmers routinely use “difference-list versions” of programs, but very little investigation has taken place into difference-list transformation. Thus, to most programmers it is either unknown that the use of difference-lists is far from safe in all contexts, or else this fact is known but attributed to Prolog’s infamous “occur check problem.” In this paper we study the transformation of list-processing programs into programs that use differencelists. In particular we are concerned with finding circumstances under which the transformation is safe. We show that dataflow analysis can be used to determine whether the transformation is applicable to a given program, thereby allowing for automatic transformation. We prove that our transformation preserves strong operational equivalence. This paper is a revised and extended version of a paper¹⁰) that was presented to theInternational Computer Science Conference 88 in Hong Kong December 1988.     

常规导弹精确打击中卫星应用效能评价

卫星导航应用由卫星系统获取航天信息,通过卫星应用系统支持作战单元,作战单元能力的增强间接反映卫星应用的效能.卫星应用的效能涉及到卫星系统、卫星应用系统及作战单元,是综合性评估问题.在系统效能、作战效能基础上,根据卫星应用的特点,提出了应用效能概念,通过作战单元能力变化评价卫星应用效能,并构建了卫星应用效能评价的指标体系...     

Towards a pipelined Prolog processor

This paper describes the design of a Prolog machine architecture and organization. Our objective was to determine the maximum performance attainable by a sequential Prolog machine for “reasonable” cost. The paper compares the organization to both general purpose micro-coded machines and reduced instruction set machines. Hand timings indicate a peak performance rate of 450 K LIPS (logical inferences per second) is well within current technology limitations and 1 M LIPS is potentially feasible.     

Visual Prolog语言在测试设备故障诊断专家系统中的应用

Visual Prolog语言是人工智能与专家系统领域最著名的逻辑程序设计语言,适合表达人的思维和推理规则,能够方便地实现模式匹配、回溯、事实数据库和谓词等功能;针对导弹测试设备结构复杂、故障隔离与定位困难等情况,充分利用Visual Prolog语言在专家系统知识表示及逻辑推理过程中的优点,建立了一个基于规则的导弹测试设备故障诊断专家系统;通过应用表明Visual Prolog语言十分适合构建此类专家系统,并具有良好的开发应用前景.     

Matlab在防护工程伪装效果评价中的应用

针对防护工程伪装效果优劣问题,给出了一种利用matlab来评价防护工程伪装效果的方法。通过分析防护工程伪装效果评价的总体架构,分别利用matlab的图像处理工具箱、统计学工具箱以及矩阵运算功能建立相关模块。实现了遥感数字图像处理、层次聚类构建指标体系、AHP确定指标权重和灰色聚类评价功能。最后通过一个实例证实运用该方法能较好满足防护工程口部伪装效果评价的需求。     

Evaluation of a compact CAD course in laboratory experiments

With the increasing deployment of CAD, the necessity of instructing employees in the use of such systems grows; short training periods are desirable. The authors developed a compact course of 40‐hour's duration in which 32 individuals (engineering students) were instructed on a 2‐dimensional CAD system; a subsequent investigation of the achievements of the course was made with the use of laboratory experiments. In qualitative and quantitative respects the performance achieved using CAD during a drawing task was lower than that attained by the same individuals at the drawing board. A compact course of the described extent can only be the basis for self‐instruction. Interrelations between the quality of the results and the method of work exist. With regard to the performance, the variance among individuals was distinctly higher at the CAD terminal than at the drawing board. A prediction concerning the achievements of the course drawn from the performance at the drawing board, especially when based on quantitative achievements, is problematic.     

Prolog to the future

The series of 'Time-Sharing System Scorecards' published from 1965-7 by the Computer Research Corp. chronicles the development of time-sharing systems in research organizations (universities and laboratories) and the expectations for commercial offerings. The last of these scorecards (reproduced in the article) shows a stage of development when time-sharing was still new enough to be a research effort and not quite mature enough to be commonplace.<>     

High performance Prolog on a RISC

This paper presents some benchmark timings from an optimising Prolog compiler using global analysis for a RISC workstation, the MIPS R2030. These results are extremely promising. For example, the infamous naive reverse benchmark runs at 2 mega LIPS. We compare these timings with those for other Prolog implementations running on the same workstation and with published timings for the KCM, a recent piece of special purpose Prolog hardware. The comparison suggests that global analysis is a fruitful source of information for an optimising Prolog compiler and that the performance of special purpose Prolog hardware can be at least matched by the code from a compiler using such information. We include some analysis of the sources of the improvement global analysis yields. An overview of the compiler is given and some implementation issues are discussed. This paper is an extended version of Ref. 15)     

Efficient Prolog: a practical tutorial

This tutorial presents twelve guidelines for making Prolog programs efficient. Topics covered include procedural versus declarative programming, internal representation of data, first-argument indexing, cuts, and ways to avoid consing.     

How to invent a Prolog machine

In this paper we study the compilation of Prolog by making visible hidden operations (especially unification), and then optimizing them using well-known partial evaluation techniques. Inspection of straightforward partially evaluated unification algorithms gives an idea how to design special abstract machine instructions which later form the target language of our compilation. We handle typical compiler problems like representation of terms explicitly. This work gives a logical reconstruction of abstract Prolog machine code, and represents an approach of constructing a correct compiler from Prolog to such a code. As an example, we are explaining the unification principles of Warren’s New Prolog Engine within our framework.     

An icon-based design method for Prolog

An icon-based design method that combines a module-oriented Prolog design model, graphical software design, and software engineering principles is presented. It is based on a dataflow-driven decomposition that is guided by design principles, followed by evaluation. Its purpose is to enable Prolog applications to be developed in accordance with the general principles of software engineering: modifiability, efficiency, reliability, and understandability. The design model and procedure are described. The design of a Lisp interpreter is considered to illustrate the method