Index to Volume 1 (1992)

Abstract

Since its introduction, APL has frequently been touted as an ideal programming language for statistical applications. Among the attractive features of APL for statistics are its extensibility, the presence of primitives for operations such as sorting, matrix inversion, and arranging data, and powerful facilities for handling matrices and other arrays. Newer programming languages incorporating some of the features of APL—notably New S and XLisp-Stat—have been designed specifically for statistical applications. Is there still a niche for APL?

We believe that APL2 continues to offer some significant benefits for statistical computation, including user-defined operators, nested arrays, and convenient implementation of arrays of any dimension. We use these characteristics of the language in the course of designing an extensible computing environment for data analysis and programming based on APL2 that incorporates some of the features of modern statistical programming languages, such as data objects, symbolic model specification, missing-data handling, and automatic search of a path of files. The system, which includes interactive statistical graphics, general linear models, and robust estimation methods, has been implemented using IBM's APL2 for PC-compatibles—both the standard version of this system and the freeware TryAPL2. The latter provides students with a free environment for modern data analysis and one in which they can explore the design of statistical software.     

Analyzing Mathematical Programs Using MProbe

Just as modern general-purpose programming languages (e.g., C++, Java) are supported by a suite of tools (debuggers, profilers, etc.), mathematical programming languages need supporting tools. MProbe is an example of a suite of tools supporting a mathematical programming language, in this case AMPL. MProbe includes tools for empirically estimating the shape of nonlinear functions of many variables, nonlinearly-constrained region shape, the effect of the objective shape on the ability to find a global optimum, tools for estimating the effectiveness of constraints and for navigating through the model, among others.     

VIBes: A Visualizer for Intervals and Boxes

VIBes is an Open Source scientific visualization system that aims at providing people working with interval methods an easy way to display results (boxes, pavings), without worrying about graphical user interface programming. It provides drawing functions accessible from multiple programming languages, without complex installation and library dependencies. VIBes is made of a visualization program and an application programming interface for popular programming languages (currently C++ and MATLAB, more are planned). It is designed for instant setup in any project and has a very short learning curve, which makes it a good visualization tool for teaching labs and tutorials. The communication between programs and VIBes goes through named-pipe or files and consists in human-readable messages. Very simple drawing functions are provided, and the VIBes viewer features navigating inside drawings and exporting images. This paper presents the main concepts driving the design of VIBes, and its software architecture. Two short programs displaying the results of a set-inversion problem and the display of projected 3-D data are provided, and future development directions are detailed.     

OSiL: An instance language for optimization

Distributed computing technologies such as Web Services are growing rapidly in importance in today’s computing environment. In the area of mathematical optimization, it is common to separate modeling languages from optimization solvers. In a completely distributed environment, the modeling language software, solver software, and data used to generate a model instance might reside on different machines using different operating systems. Such a distributed environment makes it critical to have an open standard for exchanging model instances. In this paper we present OSiL (Optimization Services instance Language), an XML-based computer language for representing instances of large-scale optimization problems including linear programs, mixed-integer programs, quadratic programs, and very general nonlinear programs. OSiL has two key features that make it much superior to current standard forms for optimization problem instances. First, it uses the object-oriented features of XML schemas to efficiently represent nonlinear expressions. Second, its XML schema maps directly into a corresponding in-memory representation of a problem instance. The in-memory representation provides a robust application program interface for general nonlinear programming, facilitates reading and writing postfix, prefix, and infix formats to and from the nonlinear expression tree, and makes the expression tree readily available for function and derivative evaluations.     

A fuzzy language

With the aim of designing and implementing programming languages that take into account the fuzzy paradigm we will modify the classical lambda calculus by adding a degree to each term and by redefining the b-reduction. Thus, for the new calculus to verify the Church–Rosser property, the degree computed with can be made through a function that is a t-norm or an s-conorm. With this new tool we design a nondeterminist language that satisfies fuzzy data programming requirements, and an example of its behaviour is shown.     

Binary fuzzy goal programming

Goal programming is an important technique for solving many decision/management problems. Fuzzy goal programming involves applying the fuzzy set theory to goal programming, thus allowing the model to take into account the vague aspirations of a decision-maker. Using preference-based membership functions, we can define the fuzzy problem through natural language terms or vague phenomena. In fact, decision-making involves the achievement of fuzzy goals, some of them are met and some not because these goals are subject to the function of environment/resource constraints. Thus, binary fuzzy goal programming is employed where the problem cannot be solved by conventional goal programming approaches. This paper proposes a new idea of how to program the binary fuzzy goal programming model. The binary fuzzy goal programming model can then be solved using the integer programming method. Finally, an illustrative example is included to demonstrate the correctness and usefulness of the proposed model.     

A reliability assessment tool for distributed software development environment based on Java and J/Link

In this paper, we propose a software reliability assessment tool based on software reliability growth models for distributed development environment by using Java programming language and J/Link technology in Mathematica. Java is an object-oriented and platform-free programming language which has several advantages such as modularization and reusability of the existing code. Especially J/Link can use and control the Mathematica kernel from a Java program. By using this J/Link technology, we can reduce some efforts to develop the tool because of reusing the existing Mathematica code used for the research. Our tool proposed here is useful for software developers in terms of the management of the system-testing process in distributed development environment.     

Program control of operating systems

The traditional job control language becomes superfluous if the existing programming languages are extended slightly. Such extensions also allow drivers and operating systems to be programmed entirely in high level languages. Ultimately, we may see machine independent operating systems. A framework is presented for an extendable operating system which allows a simple, uniform implementation of these language extensions.     

Improved Alignment-Based Algorithm for Multilingual Text Compression

Multilingual text compression exploits the existence of the same text in several languages to compress the second and subsequent copies by reference to the first. This is done based on bilingual text alignment, a mapping of words and phrases in one text to their semantic equivalents in the translation. A new multilingual text compression scheme is suggested, which improves over an immediate generalization of bilingual algorithms. The idea is to store the necessary markup data within the source language text; the incurred compression loss due to this overhead is smaller than the savings in the compressed target language texts, for a large enough number of the latter. Experimental results are presented for a parallel corpus in six languages extracted from the EUR-Lex website of the European Union. These results show the superiority of the new algorithm as a function of the number of languages.     

Machine dependent programming in common languages

It is suggested that we should distinguish between common programming languages and common solutions to specific problems. A solution may depend on specific machine characteristics even though it is expressed in a common language. It is further suggested that in future common programming languages this should be admitted openly by allowing the programmer to get access to the machine characteristics at hand through Environment Enquiries which are part of the language. Some specific examples of Environment Enquiries are given.An earlier version of this paper was published in ALGOL BULLETIN no. 18, October 1964.     

Representing Utility Functions via Weighted Goals

We analyze the expressivity, succinctness, and complexity of a family of languages based on weighted propositional formulas for the representation of utility functions. The central idea underlying this form of preference modeling is to associate numerical weights with goals specified in terms of propositional formulas, and to compute the utility value of an alternative as the sum of the weights of the goals it satisfies. We define a large number of representation languages based on this idea, each characterized by a set of restrictions on the syntax of formulas and the range of weights. Our aims are threefold. First, for each language we try to identify the class of utility functions it can express. Second, when different languages can express the same class of utility functions, one may allow for a more succinct representation than another. Therefore, we analyze the relative succinctness of languages. Third, for each language we study the computational complexity of the problem of finding the most preferred alternative given a utility function expressed in that language (© 2009 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Abstractions of control environments

This paper focusses on a language which allows to program and encapsulate control environments. The proposal is to tackle control related problems much the same way data type related problems have been tackled in recent programming language designs, that is introducing the possibility of building complex structures starting from a restricted set of primitive notions and providing a hiding mechanism allowing new objects to be used as if they were primitive in the language. An example of a control package implementing recursion along with simple exception handling mechanisms tries to put the ideas in focus.     

Understanding computer understanding of narrative text

This paper surveys recent successes in getting computers to understand human language by imbuing them with cultural knowledge and everyday common sense. The paper begins with a discussion of the centrality of language comprehension in giving computing machines their universality. Next, differences between formal programming languages currently understood by machines and properties of natural languages are discussed. The central problems of representing thought, encoding cultural knowledge, and generating inferences and cultural expectations are addressed within the context of the development of a number of computer programs dealing with narrative text. Finally, the paper ends with a discussion of the author's own computer program, BORIS, which extends the theory of language understanding and narrative comprehension in a number of directions. In particular, BORIS implements a theory of knowledge interactions, multiple perspectives, emotional reactions, parsing integrated with episodic memory, expectation failures, planning errors, and abstract narrative themes.     

Global optimization of nonconvex factorable programming problems

In this paper, we consider a special class of nonconvex programming problems for which the objective function and constraints are defined in terms of general nonconvex factorable functions. We propose a branch-and-bound approach based on linear programming relaxations generated through various approximation schemes that utilize, for example, the Mean-Value Theorem and Chebyshev interpolation polynomials coordinated with a Reformulation-Linearization Technique (RLT). A suitable partitioning process is proposed that induces convergence to a global optimum. The algorithm has been implemented in C++ and some preliminary computational results are reported on a set of fifteen engineering process control and design test problems from various sources in the literature. The results indicate that the proposed procedure generates tight relaxations, even via the initial node linear program itself. Furthermore, for nine of these fifteen problems, the application of a local search method that is initialized at the LP relaxation solution produced the actual global optimum at the initial node of the enumeration tree. Moreover, for two test cases, the global optimum found improves upon the solutions previously reported in the source literature. Received: January 14, 1998 / Accepted: June 7, 1999?Published online December 15, 2000     

On-line identification of language measure parameters for discrete-event supervisory control

The discrete-event dynamic behavior of physical plants is often represented by regular languages that can be realized as deterministic finite state automata (DFSA). The concept and construction of signed real measures of regular languages have been recently reported in literature. Major applications of the language measure are: quantitative evaluation of the discrete-event dynamic behavior of unsupervised and supervised plants; and analysis and synthesis of optimal supervisory control algorithms in the discrete-event setting. This paper formulates and experimentally validates an on-line procedure for identification of the language measure parameters based on a DFSA model of the physical plant. The recursive algorithm of this identification procedure relies on observed simulation and/or experimental data. Efficacy of the parameter identification procedure is demonstrated on the test bed of a mobile robotic system, whose dynamic behavior is modelled as a DFSA for discrete-event supervisory control.     

Dual Semidefinite Programs Without Duality Gaps for a Class of Convex Minimax Programs

In this paper, we introduce a new dual program, which is representable as a semidefinite linear programming problem, for a primal convex minimax programming problem, and we show that there is no duality gap between the primal and the dual whenever the functions involved are sum-of-squares convex polynomials. Under a suitable constraint qualification, we derive strong duality results for this class of minimax problems. Consequently, we present applications of our results to robust sum-of-squares convex programming problems under data uncertainty and to minimax fractional programming problems with sum-of-squares convex polynomials. We obtain these results by first establishing sum-of-squares polynomial representations of non-negativity of a convex max function over a system of sum-of-squares convex constraints. The new class of sum-of-squares convex polynomials is an important subclass of convex polynomials and it includes convex quadratic functions and separable convex polynomials. The sum-of-squares convexity of polynomials can numerically be checked by solving semidefinite programming problems whereas numerically verifying convexity of polynomials is generally very hard.     

From Lucid to TransLucid: Iteration, Dataflow, Intensional and Cartesian Programming

We present the development of the Lucid language from the Original Lucid of the mid-1970s to the TransLucid of today. Each successive version of the language has been a generalisation of previous languages, but with a further understanding of the problems at hand. The Original Lucid (1976), originally designed for purposes of formal verification, was used to formalise the iteration in while-loop programs. The pLucid language (1982) was used to describe dataflow networks. Indexical Lucid (1987) was introduced for intensional programming, in which the semantics of a variable was understood as a function from a universe of possible worlds to ordinary values. With TransLucid, and the use of contexts as firstclass values, programming can be understood in a Cartesian framework.      

Multiobjective transportation problem with interval cost,source and destination parameters

In this paper, we focus on the solution procedure of the multiobjective transportation problem (MOTP) where the cost coefficients of the objective functions, and the source and destination parameters have been expressed as interval values by the decision maker. This problem has been transformed into a classical MOTP where to minimize the interval objective function, the order relations that represent the decision maker's preference between interval profits have been defined by the right limit, left limit, centre, and half-width of an interval. The constraints with interval source and destination parameters have been converted into deterministic ones. Finally, the equivalent transformed problem has been solved by fuzzy programming technique. Numerical examples have been provided to illustrate the solution procedure for three possible cases of the original problem.