Testing Identifiable Kernel P Systems Using an X-machine Approach

This paper presents a testing approach for kernel P systems (kP systems), based on the X-machine testing framework and the concept of cover automaton. The testing methodology ensures that the implementation conforms the speci cations, under certain conditions, such as the identi ably concept in the context of kernel P systems

Design and Analysis of Genetically Constructed Logic Gates

Synthetic biology, comprising many aspects including in vivo, in vitro and in silico techniques, models and methods, programming paradigms and tools, is a rapidly growing field with promising potential in building new synthetically constructed devices and systems. Synthetic biology features unconventional biological systems that do not naturally exist in nature. In this paper, we discuss a software platform, Infobiotics Workbench, developed to perform in silico experiments for synthetic biology systems. We utilise the tool on an unconventional system, a genetic logic gate

A novel application of deep learning with image cropping: a smart city use case for flood monitoring

© 2020, The Author(s). Event monitoring is an essential application of Smart City platforms. Real-time monitoring of gully and drainage blockage is an important part of flood monitoring applications. Building viable IoT sensors for detecting blockage is a complex task due to the limitations of deploying such sensors in situ. Image classification with deep learning is a potential alternative solution. However, there are no image datasets of gullies and drainages. We were faced with such challenges as part of developing a flood monitoring application in a European Union-funded project. To address these issues, we propose a novel image classification approach based on deep learning with an IoT-enabled camera to monitor gullies and drainages. This approach utilises deep learning to develop an effective image classification model to classify blockage images into different class labels based on the severity. In order to handle the complexity of video-based images, and subsequent poor classification accuracy of the model, we have carried out experiments with the removal of image edges by applying image cropping. The process of cropping in our proposed experimentation is aimed to concentrate only on the regions of interest within images, hence leaving out some proportion of image edges. An image dataset from crowd-sourced publicly accessible images has been curated to train and test the proposed model. For validation, model accuracies were compared considering model with and without image cropping. The cropping-based image classification showed improvement in the classification accuracy. This paper outlines the lessons from our experimentation that have a wider impact on many similar use cases involving IoT-based cameras as part of smart city event monitoring platforms

Modelling and validating an engineering application in kernel P systems

© 2018, Springer International Publishing AG. This paper illustrates how kernel P systems (kP systems) can be used for modelling and validating an engineering application, in this case a cruise control system of an electric bike. The validity of the system is demonstrated via formal verification, carried out using the kPWorkbench tool. Furthermore, we show how the kernel P system model can be tested using automata and X-machine based techniques

On the geometry of Siegel-Jacobi domains

We study the holomorphic unitary representations of the Jacobi group based on Siegel-Jacobi domains. Explicit polynomial orthonormal bases of the Fock spaces based on the Siegel-Jacobi disk are obtained. The scalar holomorphic discrete series of the Jacobi group for the Siegel-Jacobi disk is constructed and polynomial orthonormal bases of the representation spaces are given.Comment: 15 pages, Latex, AMS fonts, paper presented at the the International Conference "Differential Geometry and Dynamical Systems", August 25-28, 2010, University Politehnica of Bucharest, Romani

Integration testing of heterotic systems

Computational theory and practice generally focus on single-paradigm systems, but relatively little is known about how best to combine components based on radically different approaches (e.g. silicon chips and wetware) into a single coherent system. In particular, while testing strategies for single-technology artefacts are generally well developed, it is unclear at present how to perform integration testing on heterotic systems: can we develop a test-set generation strategy for checking whether specified behaviours emerge (and unwanted behaviours do not) when components based on radically different technologies are combined within a single system? In this paper, we describe an approach to modelling multi-technology heterotic systems using a general-purpose formal specification strategy based on Eilenberg's X-machine model of computation. We show how this approach can be used to represent disparate technologies within a single framework, and propose a strategy for using these formal models for automatic heterotic test-set generation. We illustrate our approach by showing how to derive a test set for a heterotic system combining an X-machine-based device with a cell-based P system (membrane system)

Comparative Analysis of Statistical Model Checking Tools

Statistical model checking is a powerful and flexible approach for formal verification of computational models like P systems, which can have very large search spaces. Various statistical model checking tools have been developed, but choosing between them and using the most appropriate one requires a significant degree of experience, not only because different tools have different modelling and property specification languages, but also because they may be designed to support only a certain subset of property types. Furthermore, their performance can vary depending on the property types and membrane systems being verified. In this paper we evaluate the performance of various common statistical model checkers against a pool of biological models. Our aim is to help users select the most suitable SMC tools from among the available options, by comparing their modelling and property specification languages, capabilities and performances

Capacity for health economics research and practice in Jordan, Lebanon, the occupied Palestinian territories and Turkey: needs assessment and options for development

Background: Capacity for health economics analysis and research is indispensable for evidence-informed allocations of scarce health resources, however little is known about the experience and capacity strengthening preferences of academics and practitioners in the Eastern Mediterranean region. This study aimed to assess the needs for strengthening health economics capacity in Jordan, Lebanon, the occupied Palestinian territories and Turkey as part of the Research for Health in Conflict in Middle East and North Africa (R4HC-MENA) project. Methods: Bibliometric analysis of health economics outputs combined with an online survey of academic researchers and non-academic practitioners. The bibliometric analysis was based on a literature search conducted across seven databases. Included records were original studies and reviews with an explicit economic outcome related to health, disease or disability; had at least one author in Jordan, Lebanon, Palestine or Turkey; and were published between January 2014 and December 2018. Two types of analyses were conducted using VOSviewer software: keyword co-occurrence; and co-publication networks across countries and organizations. The online survey asked academic researchers, analysts and decision-makers – identified through the bibliometric analysis and regional professional networks – about previous exposure to and preference for capacity development in health economics. Results: Of 15,185 records returned by the literature search, 566 were included in the bibliometric analysis. Organizations in Turkey contributed more than 80% of records and had the broadest and most diverse network of collaborators, nationally and internationally. Only 1% (n=7) studies were collaborations between researchers in two or more different jurisdictions. Cost analysis, cost-effectiveness analysis and health system economics were the main health economics topics across the included studies. Economic evaluation, measuring the economic burden of disease and health equity were reported by survey respondents (n=80) as the most important areas to develop in. Short courses, learn-by-doing and mentoring from an experienced professional were, in aggregate, the most preferred capacity development modalities. Conclusions: Existing pockets of health economic expertise in the region can constitute the base of future capacity development efforts. Building confidence toward applying specific methods and trust toward stimulating cross-jurisdiction collaborations appear essential components for sustainably developing health economics capacity