Browsing Engineering and Informatics by Title
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P colonies and kernel P systemsP colonies, tissuelike P systems with very simple components, have received constant attention from the membrane computing community and in the last years several new variants of the model have been considered. Another P system model, namely kernel P system, integrating the most successfully used features of membrane systems, has recently attracted interest and some important developments have been reported. In this paper we study connections among several classes of P colonies and kernel P systems, by showing how the behaviour of these P colony systems can be represented as kernel P systems. An example illustrates the way it is modelled by using P colonies and kernel P systems and some properties of it are formally proved in the latter approach.

PADTUN  using semantic technologies in tunnel diagnosis and maintenance domainA Decision Support System (DSS) in tunnelling domain deals with identifying pathologies based on disorders present in various tunnel portions and contextual factors affecting a tunnel. Another key area in diagnosing pathologies is to identify regions of interest (ROI). In practice, tunnel experts intuitively abstract regions of interest by selecting tunnel portions that are susceptible to the same types of pathologies with some distance approximation. This complex diagnosis process is often subjective and poorly scales across cases and transport structures. In this paper, we introduce PADTUN system, a working prototype of a DSS in tunnelling domain using semantic technologies. Ontologies are developed and used to capture tacit knowledge from tunnel experts. Tunnel inspection data are annotated with ontologies to take advantage of inferring capabilities offered by semantic technologies. In addition, an intelligent mechanism is developed to exploit abstraction and inference capabilities to identify ROI. PADTUN is developed in realworld settings offered by the NeTTUN EU Project and is applied in a tunnel diagnosis use case with Société Nationale des Chemins de Fer Français (SNCF), France. We show how the use of semantic technologies allows addressing the complex issues of pathology and ROI inferencing and matching experts’ expectations of decision support.

Parameter estimation of a sixlump kinetic model of an industrial fluid catalytic cracking unitIn this work a simulation of detailed steady state model of an industrial fluid catalytic cracking (FCC) unit with a newly proposed sixlumped kinetic model which cracks gas oil into diesel, gasoline, liquefied petroleum gas (LPG), dry gas and coke. Frequency factors, activation energies and heats of reaction for the catalytic cracking kinetics and a number of model parameters were estimated using a model based parameter estimation technique along with data from an industrial FCC unit in Sudan. The estimated parameters were used to predict the major riser fractions; diesel as 0.1842 kglump/kgfeed with a 0.81% error while gasoline as 0.4863 kglump/kgfeed with a 2.71% error compared with the plant data. Thus, with good confidence, the developed kinetic model is able to simulate any type of FCC riser with sixlump model as catalysttooil (C/O) ratios were varied and the results predicted the typical riser profiles.

Parameterized Shape Grammar for nfold Generating Islamic Geometric MotifsThe complex formation of Islamic geometric Patterns (IGP) is one of the distinctive features in Islamic art and architecture. Many have attempted to reproduce these patterns in digital form, using various pattern generation techniques. Shape grammars are an effective pattern generation method, providing good aesthetic results. In this paper we present a novel approach in generating 3D IGP using an extended shape grammar: Parametrized Shape Grammar (PSG). PSG allows a user to generate both original and novel forms of Islamic geometric motifs (a repeated unit of a pattern). PSG is generalized to generate nfold Islamic geometric motifs in a 3D environment, practically implemented as a 3D modeling tool within Autodesk Maya. The parametrization within each grammar rule is the key to generating numerous original and novel Islamic geometric motifs.

Parametric covariance assignment using a reducedorder closedform covariance modelThis paper presents a novel closedform covariance model using covariance matrix decomposition for both continuoustime and discretetime stochastic systems which are subjected to Gaussian noises. Different from the existing covariance models, it has been shown that the order of the presented model can be reduced to the order of original systems and the parameters of the model can be obtained by Kronecker product and Hadamard product which imply a uniform expression. Furthermore, the associated controller design can be simplified due to the use of the reducedorder structure of the model. Based on this model, the state and output covariance assignment algorithms have been developed with parametric state and output feedback, where the computational complexity is reduced and the extended free parameters of parametric feedback supply flexibility to the optimization. As an extension, the reducedorder closedform covariance model for stochastic systems with parameter uncertainties is also presented in this paper. A simulated example is included to show the effectiveness of the proposed control algorithm, where encouraging results have been obtained.

Parametric design and optimisation of thinwalled structures for food packagingIn this paper the parametric design and functional optimisation of thinwalled structures made from plastics for food packaging is considered. These objects are produced in such vast numbers each year that one important task in the design of these objects is to minimise the amount of plastic used, subject to functional constraints, to reduce the costs of production and to conserve raw materials. By means of performing an automated optimisation on the possible shapes of the food containers, where the geometry is parametrised succinctly, a strategy to create the optimal design of the containers subject to a given set of functional constraints is demonstrated.

Parametric Representations of Facial Expressions on PDEBased SurfacesParameterisation of facial expressions on PDE surface representations of human faces are presented in this work. Taking advantage of the boundaryvalue approach inherent to BloorWilson PDE method, facial expressions are achieved by manipulating the original boundary curves. Such curves are responsible for generating a surface representation of a human face in its neutral configuration, so that regions on these curves represent a given facial expression in a fast and realistic manner. Additionally, the parameterisation proposed here is carried out by applying different mathematical transformations to the affected curves according to the corresponding facial expression. Full analytic expressions parameterising some of the most common facial expressions such as smiling and eyebrow raising are in this work. Some graphical examples of these facial expressions are used to illustrate the results obtained using BloorWilson PDE method as the foundations of the parameterisation scheme proposed here. Thus, it is shown that an efficient, intuitive and realistic parameterisation of facial expressions is attainable using BloorWilson PDE method in along with a suitable mathematical expression.

A parametric simulation on the effect of the rejected brine temperature on the performance of multieffect distillation with thermal vapour compression desalination process and its environmental impactsMultieffect distillation with thermal vapour compression (MED–TVC) is one of the most attractive thermal desalination technologies for the production of freshwater. Several mathematical models were presented in the open literature to analyse the steadystate performance of such process. However, these models have several limitations and assumptions. Therefore, there remains the challenge of having a reliable model to accurately predict the performance of the MED process. Thus, this research attempts to resolve this challenge by rectifying the shortcomings of the models found in the literature and create a new one. The robustness of the developed model is evaluated against the actual data of Umm AlNar commercial plant situated in UAE. In seawater desalinisation, a large amount of highsalinity stream (brine) is rejected back into the sea. This paper investigates the influence of the rejected (exit) brine temperature on the system performance parameters of MED–TVC process. Specifically, these parameters are considered as total heat consumption, gain output ratio, freshwater production, heat transfer area and performance ratio. Also, the particular parameters of TVC section of the entrainment ratio, compression ratio and expansion ratio are also addressed. Moreover, a critical evaluation of the influence of the rejected brine temperature on the seawater is also embedded.

Parametric study of semirigid composite connections with 3D finite element approach.This paper describes the 3dimensional finite element modelling of composite connection with steel beams and precast hollow core slab. A finite element model to simulate the structural behaviour of the composite beam was described and was used to study the behaviour of a wide range of composite connections to gain a better understanding of the structural behaviour especially the moment¿rotation characteristic of the connections. Parametric studies were carried out to investigate the structural behaviour with variations in: size of the beam, thickness of the endplate, thickness of column web, depth of precast hollow cored slab and stud spacing. Through the parametric study, the structural behaviour of the composite connection has been discussed in detail, and recommendations for the design purpose has been made.

Parametric study on composite steel beams with precast concrete hollow core floor slabsThis paper describes the finite element modelling of steel beams acting compositely with proprietary precast hollow core slabs. A companion paper (Lam D, Elliott KS, Nethercot DA. Experiments on composite steel beams with precast hollow core floor slabs. Proceedings of the Institution of Civil Engineers: Structures and Buildings 1999; in press [1]) reports results of full scale bending tests and compression slab tests. The finite element package ABAQUS was used to extend the scope of the experimental work, by first demonstrating that a 2dimensional plane stress analysis is sufficiently accurate, providing that the correct material input data and shear stud characteristics obtained from isolated pushoff tests are used. The FE results are within 5% of the experimental results. An extensive parametric study was carried out to investigate the flexural behaviour of composite beams with variations in transverse reinforcement ratio, stud spacing and steel UB section.

Parametric surface meshing for design optimisation using a PDE formulationThe problem of parametric surface meshing for the purpose of design optimisation using finite element analysis is considered. Here the surface mesh is generated as a solution of a suitably posed boundary value problem implemented on a 2D parameter space. A robust meshing scheme is presented where an initial mesh is manipulated, with the aid of the 2D parameter space, so as to obtain a suitable surface triangulation. This meshing scheme can then be used to create suitable finite element meshes with which accurate design optimisations can be carried out.

Partial differential equations for function based geometry modelling within visual cyberworldsWe propose the use of Partial Differential Equations (PDEs) for shape modelling within visual cyberworlds. PDEs, especially those that are elliptic in nature, enable surface modelling to be defined as boundaryvalue problems. Here we show how the PDE based on the Biharmonic equation subject to suitable boundary conditions can be used for shape modelling within visual cyberworlds. We discuss an analytic solution formulation for the Biharmonic equation which allows us to define a function based geometry whereby the resulting geometry can be visualised efficiently at arbitrary levels of shape resolutions. In particular, we discuss how function based PDE surfaces can be readily integrated within VRML and X3D environments

Partial Differential Equations for Geometric DesignThis title provides detailed description of how Partial Differential Equations are used in the field of geometric design, and supplies clear and concise explanations of how to implement the techniques described. It also offers extensive discussions (with examples) or practical applications of Partial Differential Equations in geometric design.

Partial Differential Equations for Modelling Wound GeometryWounds arising from various conditions are painful, embarrassing and often requires treatment plans which are costly. A crucial task, during the treatment of wounds is the measurement of the size, area and volume of the wounds. This enables to provide appropriate objective means of measuring changes in the size or shape of wounds, in order to evaluate the efficiency of the available therapies in an appropriate fashion. Conventional techniques for measuring physical properties of a wound require making some form of physical contact with it. We present a method to model a wide variety of geometries of wound shapes. The shape modelling is based on formulating mathematical boundaryvalue problems relating to solutions of Partial Differential Equations (PDEs). In order to model a given geometric shape of the wound a series of boundary functions which correspond to the main features of the wound are selected. These boundary functions are then utilised to solve an elliptic PDE whose solution results in the geometry of the wound shape. Thus, here we show how low order elliptic PDEs, such as the Biharmonic equation subject to suitable boundary conditions can be used to model complex wound geometry. We also utilise the solution of the chosen PDE to automatically compute various physical properties of the wound such as the surface area, volume and mass. To demonstrate the methodology a series of examples are discussed demonstrating the capability of the method to produce good representative shapes of wounds.

Partial ordering of weak mutually unbiased basesA quantum system (n) with variables in Z(n), where n = Qpi (with pi prime numbers), is considered. The nonnearlinear geometry G(n) of the phase space Z(n) × Z(n), is studied. The lines through the origin are factorized in terms of ‘prime factor lines’ in Z(pi)×Z(pi). Weak mutually unbiased bases (WMUB) which are products of the mutually unbiased bases in the ‘prime factor Hilbert spaces’ H(pi), are also considered. The factorization of both lines and WMUB is analogous to the factorization of integers in terms of prime numbers. The duality between lines and WMUB is discussed. It is shown that there is a partial order in the set of subgeometries of G(n), isomorphic to the partial order in the set of subsystems of (n).

Particle Acceleration Asymmetry in a Reconnecting Nonneutral Current Sheet.The acceleration of electrons and protons caused by a superDreicer electric field directed along the longitudinal component By of the magnetic field is investigated. The threecomponent magnetic field in a nonneutral current sheet occurring at the top of the reconnecting flaring loops on the charged particle trajectories and energies is considered. Particle trajectories in the reconnecting current sheet (RCS) and their energy spectra at the point of ejection from the RCS are simulated from the motion equation for different sheet thicknesses. A superDreicer electric field of the current sheet is found to accelerate particles to coherent energy spectra in a range of 10100 keV for electrons and 100400 keV for protons with energy slightly increasing with the sheet thickness. A longitudinal By component was found to define the gyration directions of particles with opposite charges toward the RCS midplane, i.e., the trajectory symmetry. For the ratio By/Bz < 106 the trajectories are fully symmetric, which results in particle ejection from an RCS as neutral beams. For the ratio By/Bz > 102 the trajectories completely lose their symmetry toward the RCS midplane, leading to the separation of particles with opposite charges into the opposite halves from an RCS midplane and the following ejection into different legs of the reconnecting loops. For the intermediate values of By/Bz the trajectories are partially symmetric toward the midplane, leading to electrons prevailing in one leg and protons in the other.

Partitioning Techniques for Reducing Computational Effort of Routing in Large Networks.A new scheme is presented for partitioning a network having a specific number of nodes and degree of connectivity such that the number of operations required to find a constrained path between a source node and destination node, averaged over all sourcedestination pairs, is minimised. The scheme can speed up the routing function, possibly by orders of magnitude under favourable conditions, at the cost of a suboptimal solution.

Passive RFID Module with LSTM Recurrent Neural Network Activity Classification Algorithm for Ambient Assisted LivingHuman activity recognition from sensor data is a critical research topic to achieve remote health monitoring and ambient assisted living (AAL). In AAL, sensors are integrated into conventional objects aimed to support targets capabilities through digital environments that are sensitive, responsive and adaptive to human activities. Emerging technological paradigms to support AAL within the home or community setting offers people the prospect of a more individually focused care and improved quality of living. In the present work, an ambient human activity classification framework that augments information from the received signal strength indicator (RSSI) of passive RFID tags to obtain detailed activity profiling is proposed. Key indices of position, orientation, mobility, and degree of activities which are critical to guide reliable clinical management decisions using 4 volunteers are employed to simulate the research objective. A twolayer, fully connected sequence long shortterm memory recurrent neural network model (LSTM RNN) is employed. The LSTM RNN model extracts the feature of RSS from the sensor data and classifies the sampled activities using SoftMax. The performance of the LSTM model is evaluated for different data size and the hyperparameters of the RNN are adjusted to optimal states, which results in an accuracy of 98.18%. The proposed framework suits well for smart health and smart homes which offers pervasive sensing environment for the elderly, persons with disability and chronic illness.