Smalltalk—80的指称语义研究

Ｓｍａｌｌｔａｌｋ－８０是原型的面向对象程序设计语言和环境，本简要地给出了Ｓｍａｌｌｔａｌｋ－８０的形式模型，并基于该模型描述了Ｓｍａｌｌｔａｌｋ－８０的静态和动态指称语义。     

Smalltalk－80的指称语义研究

Ｓｍａｌｌｔａｌｋ—８０是原型的面向对象程序设计语言和环境．本文简要地给出了Ｓｍａｌｌｔａｌｋ－８０的形式模型，并基于该模型描述了Ｓｍａｌｌｔａｌｋ—８０的静态和动态指称语义．     

Windows应用程序中的中,日文输入／输出

Ｍｉｃｒｏｓｏｆｔ Ｗｉｎｄｏｗｓ是ＭＳ－ＤＯＳ下最流行的多窗口图形用户界面环境。本文提出了一种在Ｗｉｎｄｏｗｓ应用程序中实现中、日文输入／输出的方法，该方法不同于其它一些处理方法，其特点在于：它把中、日及ＡＳＣⅡ字符的输入／输出集于一个系统之中，并在源程序一级实现，同时，该方法也可推广到其它多窗口环境及用于涉及其它非欧、美语言的Ｗｉｎｄｏｗｓ应用程序。     

“傻瓜”数据录入窗口设计原理及程序

数据库编程人员都希望系统能根据用户提供的字段名与汉字名对应表,自动生成一个漂亮的数据录入窗口,但目前所有的数据库都没有这样的功能。笔者经过对录入窗口生成过程的认真研究。找到了解决这一问题的方法。并用FoxBASE2.1编制了一个实现这一功能的过程文件。 设计原理:数据录入窗口设计主要参数有:汉字名称、字段名、数据录入格式及各位置坐标。汉字名     

关于加强Smalltalk／V分析功能的研究

本文探讨用Ｓｍａｌｌｔａｌｋ／Ｖ进行有限元分析的实现方法来加强面向对象编程的结构分析功能。基于面向对象概念的有限元方法充分体现可扩展性、易维护及软件重用的特色，为该方法智能化打下基础。     

专用汉字库的一种生成方法

本文针对一些软件在西文ＤＯＳ图形显示模式下运用专用汉字库实现汉字屏幕输出的问题，提出了一种生成专用汉字库的有效方法，并且以ＴｕｒｂｏＣ２．０为例，提供了专用汉字库的建立和在西文ＤＯＳ下使用它实现汉字屏幕输出的完整的源程序清单．     

彩色汉字窗口菜单的设计与实现

本文详细叙述了用 Turbo C 实现彩色汉字窗口菜单存在的问题及解决的方法,给出了几个主要的可以处理汉字信息的窗口操作实用函数。     

UNIX操作系统X－Window汉字系统的实现技术

本文论述了在ＵＮＩＸ操作系统Ｘ－Ｗｉｎｄｏｗ窗口环境下实现软件汉化的方法和途径，详细介绍了嵌入武汉字系统的设计思想与实现技术，包括汉字输人、输出和编辑等功能，为工作站上ＵＮＩＸ操作系统下商品化软件的汉化提供了一条可行的途径．     

中日文操作系统的设计与实现

介绍了在日文操作系统ＤＯＳ／Ｖ上增加汉字操作系统功能的设计思路，即根据ＤＯＳ／Ｖ的构成原理，利用截获日文ＩＡＥ接口调用中文输入处理模块实现汉字输入，截获日文显示／打印接口来处理汉字的打印／显示，并对汉字代码作了调整，以适应日文操作系统ＤＯＳ／Ｖ的环境．     

西文Turbo Prolog快速显示汉字方法

TurboProlog广泛用于设计人工智能程序和专家系统，它是一种说明性语言，目前使用的rurtonrologz．o版又增加了许多窗口、图形、计算功能，这使得该语言也能开发除人工智能领域以外的高质量应用程序。本人长期使用及研究TurboProlog语言，现将所开发的西文方式显示汉字方法作一介绍，以推动该语言在各领域广泛地应用。1实现原理通常西文环境下显示汉字（以16点阵汉字为例）是从字库中读取汉字的字模，并将其看成16”16点阵的图像，用画点的方法实现，这种方法显示速度较慢。笔者在编程中发现，将显示汉字看成由16条不同线型的线组成的图像…     

SPiCE: a system for translating Smalltalk programs into a Cenvironment

Smalltalk-80 (hereafter referred to as Smalltalk), which is one of the most productive programming languages/environments, is very well suited for prototyping of applications but it is less well suited for delivering applications because applications can neither run in isolation from the Smalltalk environment nor be combined with other programs written in other languages. One way to make Smalltalk suitable for delivering applications is to translate Smalltalk into a compiler language such as C. By translating Smalltalk code into portable and interoperable C code, it is possible to deliver a stand-alone version of Smalltalk applications, and to develop an application partly in Smalltalk and partly in C. However, there are some difficulties in translating Smalltalk code into such a C code. First, the execution model of Smalltalk, which creates activation records as objects, is very different from that of C, and second, Smalltalk and C have very different approaches to storage management. We have implemented SPiCE, a system for translating Smalltalk into C. Our approach to the translation is to create runtime replacement classes implementing the same functionality of Smalltalk classes that are inherently part of the Smalltalk execution model, and to provide semi-conservative real-time compacting garbage collection that works without language support     

Integration of object-oriented programming languages and database systems in KOPERNIK

KOPERNIK is an object-oriented database system, that allows uniform specification of database requests and application programs. The user interface is based on Smalltalk, and the object-oriented data model is represented in terms of classes and messages. Techniques are discussed for implementing such a model on top of an underlying relational database system. Those parts of application programs that cannot be translated into a relational language are handled by a Smalltalk processor. The semantics of the database requests is defined in terms of a meta-model and meta-messages, using an object-oriented approach. Hence we derive rules for translation of database requests into SQL queries over a binary relational view, introduced as an intermediate level between the underlying database and our conceptual view.     

Object management in a persistent smalltalk system

The main goal of the Alltalk project is to provide transparent database support to the Smalltalk programmer. As a first step towards this goal, the current version of Alltalk extends Smalltalk-80 by providing persistence to Smalltalk objects without adding a database sublanguage, new language syntax, classes or methods. This paper describes the implementation of object management in Alltalk, including database layout, database access methods, in-memory object management and high-level interface from the interpreter. It also discusses how the object manager is integrated in a unique way with the operations of the Alltalk garbage collector and interpreter.     

Interaction styles and input/output devices

Abstract

We describe the Smalltalk Gurus, components of the MoleHill intelligent tutoring system for Smalltalk programming. The Gurus offer help on plans for achieving goals in the Smalltalk environment, as well as remediation for students' incorrect and less-than-optimal plans. The Gurus' assistance is provided via the multimodal media of animation and voice-over audio. MoleHill employs multiple Gurus to deliver advice and instruction concerning disparate information domains, thus facilitating learners' cognitive organization and assimilation of new knowledge and information. We have labelled the approach instantiated by the Smalltalk Gurus the guru instructional model, one which is generally applicable to computer-based advisory systems.     

一种基于数学形态学的手写汉字方向特征提取方法

提出了一种新的基于数学形态学的手写体汉字方向特征提取的方法。该方法首先提出了一种利用数学形态学对手写汉字做笔划宽度归一化的方法，然后应用数学形态学的方向模板提取汉字在横、竖、撇、捺4个方向上的模式图像，最后，将弹性网格作用在4幅方向模式图像中，统计每个网格中的黑像素分布密度，得到汉字的方向特征。使用简单的距离分类器对120套3775个汉字手写体汉字进行识别实验，识别率达到8547％。     

Two decades of live coding and debugging of virtual machines through simulation

OpenSmalltalk-VM is a virtual machine (VM) for languages in the Smalltalk family (eg, Squeak and Pharo), which is itself written in a subset of Smalltalk that can easily be translated to C. VM development is done in Smalltalk, an activity we call “simulation.” The production VM is then derived by translating the core VM code to C. As a result, two execution models coexist: simulation, where the Smalltalk code is executed on top of a Smalltalk VM, and production, where the same code is compiled to an executable through a C compiler. The whole VM execution can be simulated: the heap is represented as a huge byte array, the VM code is executed as Smalltalk, and the native code generated by the just-in-time (JIT) compiler is executed by a processor simulator. All the Smalltalk development tools, such as the debugger, are then available while simulating. In addition, in simulation, it is also possible to use debugging features such as single stepping in the machine code generated by the JIT compiler. The Smalltalk development tools combined with the simulation debugging features provide developers with a productive environment in which to extend and debug the VM. In this article, we detail the VM simulation infrastructure and report our experiences developing and debugging VM features within it such as the garbage collector and the JIT compiler.     

Multiple multimodal mentors: delivering computer-based instruction via specialized anthropomorphic advisors

We describe the Smalltalk Gurus, components of the MoleHill intelligent tutoring system for Smalltalk programming. The Gurus offer help on plans for achieving goals in the Smalltalk environment, as well as remediation for students' incorrect and less-than-optimal plans. The Gurus' assistance is provided via the multimodal media of animation and voice-over audio. MoleHill employs multiple Gurus to deliver advice and instruction concerning disparate information domains, thus facilitating learners' cognitive organization and assimilation of new knowledge and information. We have labelled the approach instantiated by the Smalltalk Gurus the guru instructional model, one which is generally applicable to computer-based advisory systems.     

基于模糊规则和相似测量的手写汉字预分类法

文章提出了一种手写汉字预分类的新方法,该方法分两步进行,首先提取笔划密度特征并用模糊规则产生四个预分类组;然后通过模糊逻辑处理将各组字符分别转换成基于非线性加权函数的模糊样板并通过基于模糊相似测量的匹配算法、相似性测量样板的分级分类进行预分类。测试结果表明,该方法效果良好,预分类正确率达到98.17%。     

Adaptive recognition of Chinese characters: imitation ofpsychological process in machine recognition

This paper is focused on imitation of human psychological process in machine recognition of Chinese characters. Some results of research on human Chinese character recognition have been discussed and unified into a compound mechanism with an adaptive and self-developing nature. A machine imitation model has been proposed for Chinese character recognition with different routines. By some simplification but with the crucial feature of the model being retained, an experimental system for handprinted Chinese character recognition based on the novel concept has been built. Experimental results have shown that the associated routines continuously improve their performance during their work even after supervised training is halted. The routine of the global pattern approach eventually learns most of the classes and the recognition process gradually shifts from the subpattern approach to the global pattern approach     

EPS文件中矢量汉字拆分模型的研究

针对在刻字软件中人工对汉字拆分费时费力的问题,提出一个EPS文件中矢量汉字拆分模型。该模型在分析EPS文件中矢量汉字的构成特点基础上,设计了两个类以及类中方法的算法,其中的EPS文件类的算法用来读写EPS文件、拆分汉字部件,汉字部件类的算法完成移动和绘制汉字部件等功能。模型用c#语言编程实现,结果表明模型稳定、准确、高效,大大减少了人们拆字的工作量。