A good practice for making training accessible to university faculty members through ICTs: syllabus planning support training

Universal Access in the Information Society - This study focuses on a case study developed at a higher education institution, which comprises developing a new virtual teaching unit (VTU) aimed at...     

Topography of ion-etched Corning 7059 glass

Topographs of Corning 7059 glass, developed by 7Kv, 70A Ar⁺ irradiation from a hollow anode ion gun were investigated. Two forms of surface topography were observed: lens-shaped cavities and waves. These are discussed in terms of measured sputtering yield against incidence angle relation or beam divergence. Practical applications in specimen preparation for transmission electron microscopy and glass homogeneity testing are suggested.     

A review and critique on integrated production–distribution planning models and techniques

Optimisation modelling of integrated production–distribution (P–D) plans has raised significant interest among both researchers and practitioners over the past two decades. This paper provides the readers with a comprehensive review and critique on the current P–D planning and optimisation literature. We classify the published P–D planning models into seven categories based on their degree of complexity and hence capability in addressing real-life scenarios. Summary tables highlight the main characteristics of the selected models at each category. Next, the paper reclassifies and evaluates the proposed models based on the solution techniques used. Lastly, the unaddressed areas in the current literature are highlighted, important managerial implications are proposed and directions for future research in the area are suggested.     

A Pattern-Matching Compiler

Implementation of a rule-based transformation engine consists of several tasks with various abstraction levels. We present a new tool called mtom for the efficient implementation of rule-based transformations. This engine should help to bridge the gap between rewriting implementations and practical applications. It aims at implementing well-identified parts of complex applications where the use of rewriting is natural or crucial. These parts are specified using rewrite rules and integrated with the rest of the application, which is kept in a classical imperative language such as C, C++ or Java. Our tool, which can be viewed as a Yacc-like pre-processor, does not depend on a given term representation, rather it accepts implementation of terms (or term like data-types) of yet existing applications and it permits to define and execute rewrite rules upon those types. From our experiences, this system is well-suited for industrial use as well as for implementations of rule-based languages. The paper introduces several features supported by mtom.     

The kernel common vector method: a novel nonlinear subspace classifier for pattern recognition.

The common vector (CV) method is a linear subspace classifier method which allows one to discriminate between classes of data sets, such as those arising in image and word recognition. This method utilizes subspaces that represent classes during classification. Each subspace is modeled such that common features of all samples in the corresponding class are extracted. To accomplish this goal, the method eliminates features that are in the direction of the eigenvectors corresponding to the nonzero eigenvalues of the covariance matrix of each class. In this paper, we introduce a variation of the CV method, which will be referred to as the modified CV (MCV) method. Then, a novel approach is proposed to apply the MCV method in a nonlinearly mapped higher dimensional feature space. In this approach, all samples are mapped into a higher dimensional feature space using a kernel mapping function, and then, the MCV method is applied in the mapped space. Under certain conditions, each class gives rise to a unique CV, and the method guarantees a 100% recognition rate with respect to the training set data. Moreover, experiments with several test cases also show that the generalization performance of the proposed kernel method is comparable to the generalization performances of other linear subspace classifier methods as well as the kernel-based nonlinear subspace method. While both the MCV method and its kernel counterpart did not outperform the support vector machine (SVM) classifier in most of the reported experiments, the application of our proposed methods is simpler than that of the multiclass SVM classifier. In addition, it is not necessary to adjust any parameters in our approach.     

An empirical evaluation of P system testing techniques

This paper presents the existing techniques for P system testing and performs an empirical evaluation of their fault-detection efficiency. The comparison is performed using mutation testing and, based on the results obtained, some improved testing methodologies are proposed.     

Languages generated by P systems with active membranes

We propose an alternative approach to generate languages by means of P systems: building up an appropriate representation for a string by means of a corresponding membrane structure and then generating the string by visiting the membrane structure according to a well-specified strategy. To this aim, we consider P systems with active membranes, allowing membrane creation or division or duplication and dissolution, where the output of a computation may be obtained either by visiting the tree associated with the membrane structure, or by following the traces of a specific object, called traveller, or sending out the objects. For each of these approaches, we provide characterizations of recursively enumerable languages based on P systems that use different sets of operations for modifying the membrane structure. Francesco Bernardini: He started his Ph.D. at the University of Sheffield in December 2002 after having previously got a master degree in Computer Science from the University of Pisa in Italy. His research is dedicated to the study of theoretical aspects of membrane computing (P systems) and discrete models of biological systems based on P systems. Marian Gheorghe, Ph.D.: His main research interests are in computational models and their applications to software modelling and testing, formal specifications of agent based systems, software engineering. He was investigating computational power of various generative devices (regular, context-free, fully initial; grammar systems; L-systems and variants). He is currently interested in natural computing (membrane calculus) and biological modelling.     

Cognitive Factors in Programming with Diagrams

Visual programming languages aim to broaden the use ofdiagrams within the software industry, to the extentthat they are integrated into the programming languageitself. As a result, they provide an ideal opportunityto study the benefits of diagrams as an externalrepresentation during problem solving: not only isprogramming a challenging problem-solving activity,but the effect of diagram usage can be directlyassessed by comparing performance while using a visualprogramming language to performance with a standardtextual language. There have been severalmisconceptions amongst visual language researchersregarding the role of diagrams in software design, butthese are being addressed by empirical studies and bynew theories of notation design derived from studiesof visual programming. Based on this research, theauthors are able to recommend several new directionsfor research into thinking with diagrams.     

Homodyne detection and positive operator-valued measures

We describe the homodyne detector in terms of positive operator-valued measures (POV-measures) and show that in the limit the homodyne detector reproduces the detector of quadrature phase amplitude of a signal field.Work supported in part by The State Committee for Scientific Research, under the project no. 2 0227 91 01.     

Efficient parallel algorithms for path problems in directed graphs

In this paper we describe a technique for finding efficient parallel algorithms for problems on directed graphs that involve checking the existence of certain kinds of paths in the graph. This technique provides efficient algorithms for finding dominators in flow graphs, performing interval and loop analysis on reducible flow graphs, and finding the feedback vertices of a digraph. Each of these algorithms takesO(log² n) time using the same number of processors needed for fast matrix multiplication. All of these bounds are for an EREW PRAM.