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One feature of a user‐friendly system is the capability to tolerate fuzziness in the form of names or keywords. The following remarks are a first step towards a model for the intuitive human‐like notion of similarity. This model is characterized by using only the context within single words for a definition of similarity measures. These measures are based on maximal common substrings and abstract syllables. In order to obtain an efficient computation of this formal similarity in large lists, a preselection method is given which uses a simple distance between strings and a precomputed binary relation between character‐pairs and keywords.

The purpose of this paper is to present a solution strategy for the analysis of cable networks which includes an extension to the force density method (FDM) in an attempt to support cable elements when they become slack. The ability to handle slack cable elements in the analysis is particularly important especially in cases where the original cable lengths are predefined, i.e. the cable structure has already been constructed, and there is a need for further analysis to account for additional loading such as wind. The solution strategy is implemented in a software application.

The development of the software required the implementation of the FDM for the analysis of cable networks and its extension to handle constraints. The implemented constraints included the ability to preserve the length in the stressed or the unstressed state of predefined cable elements. In addition, cable statics are incorporated with the development of the cable equation and its modification to be able to be handled by the FDM .

The implementation of the solution strategy is presented through examples using the software which has been developed for these purposes.

The results suggest that for cable networks spanning large distances or cable elements with considerable self-weight the neglect of the cable slackening effects is not always conservative.

Not only does the problem of correcting spelling errors by computer have a long history, it is evidently of considerable current interest as papers and letters on the topic continue to appear rapidly. This is not surprising, since techniques useful in detecting and correcting mis‐spellings normally have other important applications. Moreover, both the power of small computers and the routine production of machine‐readable text have increased enormously over the last decade to the point where automatic spelling error detection/correction has become not only feasible but highly desirable.

This paper provides an introduction to the use of n‐grams in textual information systems, where an n‐gram is a string of n, usually adjacent, characters extracted from a section of continuous text. Applications that can be implemented efficiently and effectively using sets of n‐grams include spelling error detection and correction, query expansion, information retrieval with serial, inverted and signature files, dictionary look‐up, text compression, and language identification.

The present paper describes a Fortran library FLIPP constituting a run‐time environment that is linked to scientific applications software (such as finite‐element analysis programs) to support programming of interactive program control and use of persistent user‐defined dynamic data structures. The system consists of control and data definition and manipulation subsystems. The FLIPP routines are fully‐portable standard Fortran 77 procedures and the use of FLIPP leads the programmer to information hiding, e.g. as in object‐oriented systems. Program design and maintenance are facilitated to a considerable degree, while at the same time the performance of the programs using the FLIPP system remains fairly good as demonstrated by the examples.

The aim of this article is to obtain a stable tensegrity structure by using the minimum knowledge of the structure.

Three methods have been formulated based on the eigen value decomposition (EVD) and singular value decomposition theorems. These two theorems are being implemented on the matrices, which are computed from the minimal data of the structure. The required minimum data for the structure is the dimension of the structure, the connectivity matrix of the structure and the initial force density matrix computed from the type of elements. The stability of the structure is analyzed based on the rank deficiency of the force density matrix and equilibrium matrix.

The main purpose of this article is to use the defined methods to find (1) the nodal coordinates of the structure, (2) the final force density values of the structure, (3) single self-stress from multiple self-stresses and (4) the stable structure.

By using the defined approaches, one can understand the difference of each method, which includes, (1) the selection of eigenvalues, (2) the selection of nodal coordinates from the first decomposition theorem, (3) the selection of mechanism mode and force density values further and (4) the solution of single feasible self-stress from multiple self-stresses.

The determination of feasible self-stress modes and grouping of elements for tensegrities with predefined geometry and multiple self-stress modes is very important, though difficult, in the design of these structures. The purpose of this paper is to present a novel approach to the automated element grouping and self-stress identification of tensegrities.

A set of feasible solutions conforming to the unilateral behaviour of elements is obtained through an optimisation process, which is solved using a genetic algorithm. Each chromosome in the population having a negative fitness is a distinctive feasible solution with its own grouping characteristic, which is automatically determined throughout the evolution process.

The self-stress identification is formulated through an unconstrained minimisation problem. The objective function of this minimisation problem is defined in such a way that takes into account both the feasibility of a solution and grouping of elements. The method generates a set of feasible self-stress modes rather than a single one and automatically and simultaneously suggests a grouping of elements for every feasible self-stress mode. A self-stress mode with a minimal/subminimal grouping of elements is also obtained.

The method can efficiently generate sets of feasible solutions rather than a single one. The authors also address one of the challenging issues related to this identification, i.e., automated grouping of elements. These features makes the method very efficient since most of the state-of-the-art methods address the self-stress identification of tensegrities based on predefined groupings of elements whilst providing only a single corresponding solution.

Considers the material impact of computers and cybernetics in the 1980s. Summarizes some of the then current principal applications. Looks at the contribution made by cybernetics to computer development in the period 1940‐1981. Emphasises the widely held belief of the day that “anyone must have some understanding of computers and their operation to understand much about cybernetics”. The re‐published work served as a guide and introduction to using the digital computers of the 1980s in systems and cybernetics research and developments and was one in a series of 12 texts prepared by some well‐known cyberneticians and systemists on important topics in these inter‐ and trans‐disciplinary sciences.

The purpose of this paper is to compare the use of two Object-Relational models against the use of a post-Relational model for a realistic application. Although real-world applications, in most cases, can be adequately modeled by the Entity-Relationship (ER) model, the transformation to the popular Relational model alters the representation of structures common in reality, like multi-valued and composite fields. Alternative database models have been developed to overcome these shortcomings.

Based on the ER model of a medical application, this paper compares the information representation, manipulation and enforcement of integrity constraints through PostgreSQL and Oracle, against the use of a post-Relational model composed of the Conceptual Universal Database Language (CUDL) and the Conceptual Universal Database Language Abstraction Level (CAL).

The CAL/CUDL pair, although more periphrastic for data definition, is simpler for data insertions, does not require the use of procedural code for data updates, produces clearer output for retrieval of attributes, can accomplish retrieval of rows based on conditions that address composite data with declarative statements and supports data validation for relationships between composite data without the need for procedural code.

To verify, in practice, the conclusions of the paper, complete implementation of a CAL/CUDL system is needed.

The use of the CAL/CUDL pair would advance the productivity of database application development.

This paper highlights the properties of realistic database-applications modelling and management that are desirable by developers and shows that these properties are better satisfied by the CAL/CUDL pair.

With an increase in the amount of multilingual content on the World Wide Web, users are often striving to access information provided in a language of which they are non-native speakers. The purpose of this paper is to present a comprehensive study of user profile representation techniques and investigate their use in personalized cross-language information retrieval (CLIR) systems through the means of personalized query expansion.

The user profiles consist of weighted terms computed by using frequency-based methods such as tf-idf and BM25, as well as various latent semantic models trained on monolingual documents and cross-lingual comparable documents. This paper also proposes an automatic evaluation method for comparing various user profile generation techniques and query expansion methods.

Experimental results suggest that latent semantic-weighted user profile representation techniques are superior to frequency-based methods, and are particularly suitable for users with a sufficient amount of historical data. The study also confirmed that user profiles represented by latent semantic models trained on a cross-lingual level gained better performance than the models trained on a monolingual level.

Previous studies on personalized information retrieval systems have primarily investigated user profiles and personalization strategies on a monolingual level. The effect of utilizing such monolingual profiles for personalized CLIR remains unclear. The current study fills the gap by a comprehensive study of user profile representation for personalized CLIR and a novel personalized CLIR evaluation methodology to ensure repeatable and controlled experiments can be conducted.