A framework and tool support for the systematic testing of model-based specifications

Formal specifications can precisely and unambiguously define the required behavior of a software system or component. However, formal specifications are complex artifacts that need to be verified to ensure that they are consistent, complete, and validated against the requirements. Specification testing or animation tools exist to assist with this by allowing the specifier to interpret or execute the specification. However, currently little is known about how to do this effectively. This article presents a framework and tool support for the systematic testing of formal, model-based specifications. Several important generic properties that should be satisfied by model-based specifications are first identified. Following the idea of mutation analysis, we then use variants or mutants of the specification to check that these properties are satisfied. The framework also allows the specifier to test application-specific properties. All properties are tested for a range of states that are defined by the tester in the form of a testgraph, which is a directed graph that partially models the states and transitions of the specification being tested. Tool support is provided for the generation of the mutants, for automatically traversing the testgraph and executing the test cases, and for reporting any errors. The framework is demonstrated on a small specification and its application to three larger specifications is discussed. Experience indicates that the framework can be used effectively to test small to medium-sized specifications and that it can reveal a significant number of problems in these specifications.

On a resampling approach for tests on the number of clusters with mixture model-based clustering of tissue samples

We consider the problem of assessing the number of clusters in a limited number of tissue samples containing gene expressions for possibly several thousands of genes. It is proposed to use a normal mixture model-based approach to the clustering of the tissue samples. One advantage of this approach is that the question on the number of clusters in the data can be formulated in terms of a test on the smallest number of components in the mixture model compatible with the data. This test can be carried out on the basis of the likelihood ratio test statistic, using resampling to assess its null distribution. The effectiveness of this approach is demonstrated on simulated data and on some microarray datasets, as considered previously in the bioinformatics literature. (C) 2004 Elsevier Inc. All rights reserved.

Speeding up the EM algorithm for mixture model-based segmentation of magnetic resonance images

Mixture models implemented via the expectation-maximization (EM) algorithm are being increasingly used in a wide range of problems in pattern recognition such as image segmentation. However, the EM algorithm requires considerable computational time in its application to huge data sets such as a three-dimensional magnetic resonance (MR) image of over 10 million voxels. Recently, it was shown that a sparse, incremental version of the EM algorithm could improve its rate of convergence. In this paper, we show how this modified EM algorithm can be speeded up further by adopting a multiresolution kd-tree structure in performing the E-step. The proposed algorithm outperforms some other variants of the EM algorithm for segmenting MR images of the human brain. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

Right ventricle extraction by low level and model-based algorithm

In this paper we present an algorithm as the combination of a low level morphological operation and model based Global Circular Shortest Path scheme to explore the segmentation of the Right Ventricle. Traditional morphological operations were employed to obtain the region of interest, and adjust it to generate a mask. The image cropped by the mask is then partitioned into a few overlapping regions. Global Circular Shortest Path algorithm is then applied to extract the contour from each partition. The final step is to re-assemble the partitions to create the whole contour. The technique is deemed quite reliable and robust, as this is illustrated by a very good agreement between the extracted contour and the expert manual drawing output.

Nootropia : a user profiling model based on a self-organising term network

Artificial Immune Systems are well suited to the problem of using a profile representation of an individual’s or a group’s interests to evaluate documents. Nootropia is a user profiling model that exhibits similarities to models of the immune system that have been developed in the context of autopoietic theory. It uses a self-organising term network that can represent a user’s multiple interests and can adapt to both short-term variations and substantial changes in them. This allows Nootropia to drift, constantly following changes in the user’s multiple interests, and, thus, to become structurally coupled to the user.

A co-cultured skin model based on cell support membranes

Tissue engineering of skin based on collagen:PCL biocomposites using a designed co-culture system is reported. The collagen:PCL biocomposites having collagen:PCL (w/w) ratios of 1:4, 1:8, and 1:20 have been proven to be biocompatible materials to support both adult normal human epidermal Keratinocyte (NHEK) and mouse 3T3 fibroblast growth in cell culture, respectively, by Dai, Coombes, et al. in 2004. Films of collagen:PCL biocomposites were prepared using non-crosslinking method by impregnation of lyophilized collagen mats with PCL/dichloromethane solutions followed by solvent evaporation. To mimic the dermal/epidermal structure of skin, the 1:20 collagen:PCL biocomposites were selected for a feasibility study of a designed co-culture technique that would subsequently be used for preparing fibroblast/biocomposite/keratinocyte skin models. A 55.3% increase in cell number was measured in the designed co-culture system when fibroblasts were seeded on both sides of a biocomposite film compared with cell culture on one surface of the biocomposite in the feasibility study. The co-culture of human keratinocytes and 3T3 fibroblasts on each side of the membrane was therefore studied using the same co-culture system by growing keratinocytes on the top surface of membrane for 3 days and 3T3 fibroblasts underneath the membrane for 6 days. Scanning electron microscopy (SEM) and immunohistochemistry assay revealed good cell attachment and proliferation of both human keratinocytes and 3T3 fibroblasts with these two types of cells isolated well on each side of the membrane. Using a modified co-culture technique, a co-cultured skin model presenting a confluent epidermal sheet on one side of the biocomposite film and fibroblasts populated on the other side of the film was developed successfully in co-culture system for 28 days under investigations by SEM and immunohistochemistry assay. Thus, the design of a co-culture system based on 1:20 (w/w) collagen:PCL biocomposite membranes for preparation of a bi-layered skin model with differentiated epidermal sheet was proven in principle. The approach to skin modeling reported here may find application in tissue engineering and screening of new pharmaceuticals. © 2005 Elsevier Inc. All rights reserved.