Trace Semantics for the Owicki-Gries Theory Integrated with the Progress Logic from UNITY

The theory of Owicki and Gries has been used as a platform for safety-based verifcation and derivation of concurrent programs. It has also been integrated with the progress logic of UNITY which has allowed newer techniques of progress-based verifcation and derivation to be developed. However, a theoretical basis for the integrated theory has thus far been missing. In this paper, we provide a theoretical background for the logic of Owicki and Gries integrated with the logic of progress from UNITY. An operational semantics for the new framework is provided which is used to prove soundness of the progress logic.

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

Measurement and state preparation via ion trap quantum computing

We investigate in detail the effects of a QND vibrational number measurement made on single ions in a recently proposed measurement scheme for the vibrational state of a register of ions in a linear rf trap [C. D'HELON and G. J. MILBURN, Phys Rev. A 54, 5141 (1996)]. The performance of a measurement shows some interesting patterns which are closely related to searching.

Data grid for the management, reconstruction, analysis and visualisation of archaeological data

In 2007 Associate Professor Jay Hall retires from the University of Queensland after more than 30 years of service to the Australian archaeological community. Celebrated as a gifted teacher and a pioneer of Queensland archaeology, Jay leaves a rich legacy of scholarship and achievement across a wide range of archaeological endeavours. An Archæological Life brings together past and present students, colleagues and friends to celebrate Jay’s contributions, influences and interests.

Geração de modelos digitais de superfície por meio de plataformas computacionais com estrutura vetorial e raster

Geographic Information Systems (GIS) integrate the technologies related to Geoprocessing, with the ability to manipulate georeferenced information through data storage, management and analysis. One of the GIS applications is the generation of Digital Elevation Models (DEM) as a result of rebuilding the elevation of a region using computation tools and artificial representation. This paper presents the DEM created from a point base in two computational frameworks with different structures (vector and raster), comparing the contour lines generated from these models with the original contour lines from analog cartographic base. It was observed that one of the generated models presented some discrepancies related to real space for both GIS structures. However, using constrained Delaunay's triangulation in raster GIS a digital elevation model was generated with contour lines quite close to the original ones, with satisfactory results. A 3-D terrain representation was also created offering a very useful tool for analysis.

Irreducible 2-fold cycle systems

In this paper, it is shown that for any pair of integers (m, n) with 4 ≤ m ≤ n, if there exists an m-cycle system of order n, then there exists an irreducible 2-fold m-cycle system of order n, except when (m, n) = (5,5). A similar result has already been established for the case of 3-cycles. © 2005 Wiley Periodicals, Inc.

Procedure compilation in the refinement calculus

High-level language program compilation strategies can be proven correct by modelling the process as a series of refinement steps from source code to a machine-level description. We show how this can be done for programs containing recursively-defined procedures in the well-established predicate transformer semantics for refinement. To do so the formalism is extended with an abstraction of the way stack frames are created at run time for procedure parameters and variables.

On Hamilton cycle decomposition of 6-regular circulant graphs

The circulant graph Sn, where S ⊆ Zn \ {0}, has vertex set Zn and edge set {{x, x + s}|x ∈ Zn, s ∈ S}. It is shown that there is a Hamilton cycle decomposition of every 6-regular circulant graph Sn in which S has an element of order n.

Computational methods for the detection of facial palsy

We are developing a telemedicine application which offers automated diagnosis of facial (Bell's) palsy through a Web service. We used a test data set of 43 images of facial palsy patients and 44 normal people to develop the automatic recognition algorithm. Three different image pre-processing methods were used. Machine learning techniques (support vector machine, SVM) were used to examine the difference between the two halves of the face. If there was a sufficient difference, then the SVM recognized facial palsy. Otherwise, if the halves were roughly symmetrical, the SVM classified the image as normal. It was found that the facial palsy images had a greater Hamming Distance than the normal images, indicating greater asymmetry. The median distance in the normal group was 331 (interquartile range 277-435) and the median distance in the facial palsy group was 509 (interquartile range 334-703). This difference was significant (P