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  • Examining citizens' perceived value of internet of things technologies in facilitating public sector services engagement

    El-Haddadeh, R.; Weerakkody, Vishanth J.P.; Osmani, M.; Thakker, Dhaval; Kapoor, K.K. (2018)
    With the advancement of disruptive new technologies, there has been a considerable focus on personalisation as an important component in nurturing users' engagement. In the context of smart cities, Internet of Things (IoT) offer a unique opportunity to help empower citizens and improve societies' engagement with their governments at both micro and macro levels. This study aims to examine the role of perceived value of IoT in improving citizens' engagement with public services. A survey of 313 citizens in the UK, engaging in various public services, enabled through IoT, found that the perceived value of IoT is strongly influenced by empowerment, perceived usefulness and privacy related issues resulting in significantly affecting their continuous use intentions. The study offers valuable insights into the importance of perceived value of IoT-enabled services, while at the same time, providing an intersectional perspective of UK citizens towards the use of disruptive new technologies in the public sector.
  • An automatic corneal subbasal nerve registration system using FFT and phase correlation techniques for an accurate DPN diagnosis

    Al-Fahdawi, Shumoos; Qahwaji, Rami S.R.; Al-Waisy, Alaa S.; Ipson, Stanley S. (2015)
    Confocal microscopy is employed as a fast and non-invasive way to capture a sequence of images from different layers and membranes of the cornea. The captured images are used to extract useful and helpful clinical information for early diagnosis of corneal diseases such as, Diabetic Peripheral Neuropathy (DPN). In this paper, an automatic corneal subbasal nerve registration system is proposed. The main aim of the proposed system is to produce a new informative corneal image that contains structural and functional information. In addition a colour coded corneal image map is produced by overlaying a sequence of Cornea Confocal Microscopy (CCM) images that differ in their displacement, illumination, scaling, and rotation to each other. An automatic image registration method is proposed based on combining the advantages of Fast Fourier Transform (FFT) and phase correlation techniques. The proposed registration algorithm searches for the best common features between a number of sequenced CCM images in the frequency domain to produce the formative image map. In this generated image map, each colour represents the severity level of a specific clinical feature that can be used to give ophthalmologists a clear and precise representation of the extracted clinical features from each nerve in the image map. Moreover, successful implementation of the proposed system and the availability of the required datasets opens the door for other interesting ideas; for instance, it can be used to give ophthalmologists a summarized and objective description about a diabetic patient’s health status using a sequence of CCM images that have been captured from different imaging devices and/or at different times
  • A Robust Face Recognition System Based on Curvelet and Fractal Dimension Transforms

    Al-Waisy, Alaa S.; Qahwaji, Rami S.R.; Ipson, Stanley S.; Al-Fahdawi, Shumoos (2015)
    n this paper, a powerful face recognition system for authentication and identification tasks is presented and a new facial feature extraction approach is proposed. A novel feature extraction method based on combining the characteristics of the Curvelet transform and Fractal dimension transform is proposed. The proposed system consists of four stages. Firstly, a simple preprocessing algorithm based on a sigmoid function is applied to standardize the intensity dynamic range in the input image. Secondly, a face detection stage based on the Viola-Jones algorithm is used for detecting the face region in the input image. After that, the feature extraction stage using a combination of the Digital Curvelet via wrapping transform and a Fractal Dimension transform is implemented. Finally, the K-Nearest Neighbor (K-NN) and Correlation Coefficient (CC) Classifiers are used in the recognition task. Lastly, the performance of the proposed approach has been tested by carrying out a number of experiments on three well-known datasets with high diversity in the facial expressions: SDUMLA-HMT, Faces96 and UMIST datasets. All the experiments conducted indicate the robustness and the effectiveness of the proposed approach for both authentication and identification tasks compared to other established approaches.
  • A Fast and Accurate Iris Localization Technique for Healthcare Security System

    Al-Waisy, Alaa S.; Qahwaji, Rami S.R.; Ipson, Stanley S.; Al-Fahdawi, Shumoos (2015)
    In the health care systems, a high security level is required to protect extremely sensitive patient records. The goal is to provide a secure access to the right records at the right time with high patient privacy. As the most accurate biometric system, the iris recognition can play a significant role in healthcare applications for accurate patient identification. In this paper, the corner stone towards building a fast and robust iris recognition system for healthcare applications is addressed, which is known as iris localization. Iris localization is an essential step for efficient iris recognition systems. The presence of extraneous features such as eyelashes, eyelids, pupil and reflection spots make the correct iris localization challenging. In this paper, an efficient and automatic method is presented for the inner and outer iris boundary localization. The inner pupil boundary is detected after eliminating specular reflections using a combination of thresholding and morphological operations. Then, the outer iris boundary is detected using the modified Circular Hough transform. An efficient preprocessing procedure is proposed to enhance the iris boundary by applying 2D Gaussian filter and Histogram equalization processes. In addition, the pupil’s parameters (e.g. radius and center coordinates) are employed to reduce the search time of the Hough transform by discarding the unnecessary edge points within the iris region. Finally, a robust and fast eyelids detection algorithm is developed which employs an anisotropic diffusion filter with Radon transform to fit the upper and lower eyelids boundaries. The performance of the proposed method is tested on two databases: CASIA Version 1.0 and SDUMLA-HMT iris database. The Experimental results demonstrate the efficiency of the proposed method. Moreover, a comparative study with other established methods is also carried out.
  • Laminar and turbulent analytical dam break wave modelling on dry-downstream open channel flow

    Taha, T.; Lateef, A.O.A.; Pu, Jaan H. (2018-09)
    A dam break wave caused by the discontinuity in depth and velocity of a flow is resulted from instantaneous release a body of water from a channel and classified naturally as a rapidly varied unsteady flow. Due to its nature, it is hard to be accurately represented by analytical models. The aim of this study is to establish the modelling differences and complexity echelons between analytically simulated explicit laminar and turbulent dry bed dam break wave free surface profiles. An in-depth solution to the free surface profile has been provided and evaluated by representing the reported dam break flow measurements at various locations. The methodology adopted utilizes the free surface profile formulations presented by Chanson 1,2, which are developed using the method of characteristics. In order to validate the results of the presented analytical models in illustrating the dam break wave under dry bed conditions, published experimental data provided by Schoklitsch 3, Debiane 4 and Dressler 5 are used to compare and analyze the performance of the dam break waves under laminar and turbulent flow conditions.
  • P colonies and kernel P systems

    Csuhaj-Varju, E.; Gheorghe, Marian; Lefticaru, Raluca (2018-09)
    P colonies, tissue-like 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.
  • The wild bootstrap resampling in regression imputation algorithm with a Gaussian Mixture Model

    Mat Jasin, A.; Neagu, Daniel; Csenki, Attila (2018-07)
    Unsupervised learning of finite Gaussian mixture model (FGMM) is used to learn the distribution of population data. This paper proposes the use of the wild bootstrapping to create the variability of the imputed data in single miss-ing data imputation. We compare the performance and accuracy of the proposed method in single imputation and multiple imputation from the R-package Amelia II using RMSE, R-squared, MAE and MAPE. The proposed method shows better performance when compared with the multiple imputation (MI) which is indeed known as the golden method of missing data imputation techniques.
  • A Comparison between Vector Algorithm and CRSS Algorithms for Indoor Localization using Received Signal Strength

    Obeidat, Huthifa A.N.; Dama, Yousif A.S.; Abd-Alhameed, Raed A.; Hu, Yim Fun; Qahwaji, Rami S.R.; Noras, James M.; Jones, Steven M.R. (2016)
    A comparison is presented between two indoor localization algorithms using received signal strength, namely the vector algorithm and the Comparative Received Signal Strength (CRSS) algorithm. Signal values were obtained using ray tracing software and processed with MATLAB to ascertain the effects on localization accuracy of radio map resolution, number of access points and operating frequency. The vector algorithm outperforms the CRSS algorithm, which suffers from ambiguity, although that can be reduced by using more access points and a higher operating frequency. Ambiguity is worsened by the addition of more reference points. The vector algorithm performance is enhanced by adding more access points and reference points while it degrades with increasing frequency provided that the statistical mean of error increased to about 60 cm for most studied cases.
  • Analysis of cloud-based e-government services acceptance in Jordan: challenges and barriers

    Alkhwaldi, A.F.A.; Kamala, Mumtaz A.; Qahwaji, Rami S.R. (2018-06)
    There is increasing evidence that the Cloud Computing services have become a strategic direction for governments' IT work by the dawn of the third-millennium. The inevitability of this computing technology has been recognized not only in the developed countries like the UK, USA and Japan, but also in the developing countries like the Middle East region and Malaysia, who have launched migrations towards Cloud platforms for more flexible, open, and collaborative public services. In Jordan, the cloud-based e-government project has been deemed as one of the high priority areas for the government agencies. In spite of its phenomenal evolution, various governmental cloud-based services still facing adoption challenges of e-government projects like technological, human-aspects, social, and financial which need to be treated and considered carefully by any government agency contemplating its implementation. While there have been extensive efforts to investigate the e-government adoption from the citizens' perspective using different theories and models, none have paid adequate attention to the security issues. This paper explores the different perspectives of the extent in which these challenges inhibit the acceptance and use of cloud computing in Jordanian public sector. In addition to examining the effect of these challenges on the participants’ security perception. The empirical evidence provided a total of 220 valid responses to our online questionnaire from Jordanian citizens including IT- staff from different government sectors. Based on the data analysis some significant challenges were identified. The results can help the policy makers in the public sector to guide successful acceptance and adoption of cloud-based e-government services in Jordan.
  • Performance analysis of hybrid system of multi effect distillation and reverse osmosis for seawater desalination via modeling and simulation

    Filippini, G.; Al-Obaidi, M.A.; Manenti, F.; Mujtaba, Iqbal M. (2018)
    The coupling of thermal (Multi Stage Flash, MSF) and membrane processes (Reverse Osmosis, RO) in desalination systems has been widely presented in the literature to achieve an improvement of performance compared to an individual process. However, very little study has been made to the combined Multi Effect Distillation (MED) and Reverse Osmosis (RO) processes. Therefore, this research investigates several design options of MED with thermal vapor compression (MED_TVC) coupled with RO system. To achieve this aim, detailed mathematical models for the two processes are developed, which are independently validated against the literature. Then, the integrated model is used to investigate the performance of several configurations of the MED_TVC and RO processes in the hybrid system. The performance indicators include the fresh water productivity, energy consumption, fresh water purity, and recovery ratio. Basically, the sensitivity analysis for each configuration is conducted with respect to seawater conditions and steam supply variation. Most importantly, placing the RO membrane process upstream in the hybrid system generates the overall best configuration in terms of the quantity and quality of fresh water produced. This is attributed to acquiring the best recovery ratio and lower energy consumption over a wide range of seawater salinity.
  • The Influence of Lubricant Degradation on Measured Piston Ring Film Thickness in a Fired Gasoline Reciprocating Engine

    Notay, Rai S.; Priest, Martin; Fox, M.F. (2019-01)
    A laser induced fluorescence system has been developed to visualise the oil film thickness between the piston ring and cylinder wall of a fired gasoline engine via a small optical window mounted in the cylinder wall. A fluorescent dye was added to the lubricant in the sump to allow the lubricant to fluoresce when absorbing laser radiation. The concentration of the dye did not disturb the lubricant chemistry or its performance. Degraded engine oil samples were used to investigate the influence of lubricant quality on ring pack lubricant film thickness measurements. The results show significant differences in the lubricant film thickness profiles for the ring pack when the lubricant degrades which will affect ring pack friction and ultimately fuel economy.
  • Performance evaluation of multi-stage reverse osmosis process with permeate and retentate recycling strategy for the removal of chlorophenol from wastewater

    Al-Obaidi, M.A.; Kara-Zaitri, Chakib; Mujtaba, Iqbal M. (2018)
    Reverse Osmosis (RO) is one of the most widely used technologies for wastewater treatment for the removal of toxic impurities, such as phenol and phenolic compounds from industrial effluents. In this research, performance of multi-stage RO wastewater treatment system is evaluated for the removal of chlorophenol from wastewater using model-based techniques. A number of alternative configurations with recycling of permeate, retentate, and permeate-retentate streams are considered. The performance is measured in terms of total recovery rate, permeate product concentration, overall chlorophenol rejection and energy consumption and the effect of a number of operating parameters on the overall performance of the alternative configurations are evaluated. The results clearly show that the permeate recycling scheme at fixed plant feed flow rate can remarkably improve the final chlorophenol concentration of the product despite a reduction in the total recovery rate.
  • Crystallization of calcium carbonate and magnesium hydroxide in the heat exchangers of once-through multistage flash (MSF-OT) desalination process

    Alsadaie, S.; Mujtaba, Iqbal M. (2018)
    In this paper, a dynamic model of fouling is presented to predict the crystallization of calcium carbonate and magnesium hydroxide inside the condenser tubes of Once-Through Multistage Flash (MSF-OT) desalination process. The model considers the combination of kinetic and mass diffusion rates taking into account the effect of temperature, velocity and salinity of the seawater. The equations for seawater carbonate system are used to calculate the concentration of the seawater species. The effects of salinity and temperature on the solubility of calcium carbonate and magnesium hydroxide are also considered. The results reveal an increase in the fouling inside the tubes caused by crystallization of CaCO3 and Mg(OH)2 with increase in the stage temperature. The intake seawater temperature and the Top Brine Temperature (TBT) are varied to investigate their impact on the fouling process. The results show that the (TBT) has greater impact than the seawater temperature on increasing the fouling.
  • Robustness of Automotive SOTA: State-of-the-art in Uncertainty Modelling

    Murphy, O.; Habib Zadeh, Esmaeil; Campean, I. Felician; Neagu, Daniel (2018-06-28)
    This paper identifies the need for thorough experimental based study for Software-over-the-air (SOTA) in an automotive context. The paper outlines the challenges and context for automotive SOTA with an extensive literature review. It then details the early stages of the experimental studies, which aim to identify the key control and noise factors that affect performance of the SOTA in an automotive environment. This contribution establishes a framework for uncertainty modelling of SOTA as a system which highlights the needs to develop solutions requiring big data gathering and analysis as next research opportunities to the scientific community.
  • Exploring Methods for Comparing Similarity of Dimensionally Inconsistent Multivariate Numerical Data

    Micic, Natasha; Neagu, Daniel; Torgunov, Denis; Campean, I. Felician (2018-06-28)
    When developing multivariate data classification and clustering methodologies for data mining, it is clear that most literature contributions only really consider data that contain consistently the same attributes. There are however many cases in current big data analytics applications where for same topic and even same source data sets there are differing attributes being measured, for a multitude of reasons (whether the specific design of an experiment or poor data quality and consistency). We define this class of data a dimensionally inconsistent multivariate data, a topic that can be considered a subclass of the Big Data Variety research. This paper explores some classification methodologies commonly used in multivariate classification and clustering tasks and considers how these traditional methodologies could be adapted to compare dimensionally inconsistent data sets. The study focuses on adapting two similarity measures: Robinson-Foulds tree distance metrics and Variation of Information; for comparing clustering of hierarchical cluster algorithms (such clusters are derived from the raw multivariate data). The results from experiments on engineering data highlight that adapting pairwise measures to exclude non-common attributes from the traditional distance metrics may not be the best method of classification. We suggest that more specialised metrics of similarity are required to address challenges presented by dimensionally inconsistent multivariate data, with specific applications for big engineering data analytics.
  • Formal Modelling of Cruise Control System Using Event-B and Rodin Platform

    Predut, S.; Ipate, F.; Gheorghe, Marian; Campean, I. Felician (2018-06-28)
    Formal modelling is essential for precisely defining, understanding and reasoning when designing complex systems, such as cyberphysical systems. In this paper we present a formal specification using Event-B and Rodin platform for a case study of a cruise control system for a hybrid propulsion vehicle and electric bicycle (e-Bike). Our work uses the EventB method, a formal approach for reliable systems specification and verification, being supported by the Rodin platform, based on theorem proving, allowing a stepwise specification process based on refinement. We also use, from the same platform, the ProB model checker for the verification of the B-Machine and iUML plug-in to visualize our model. This approach shows the benefits of using a formal modelling platform, in the context of cyberphysical systems, which provides multiple ways of analysing a system.
  • Prediction of the depth-averaged two-dimensional flow direction along a meander in compound channels

    Shan, Y.; Huang, S.; Liu, C.; Guo, Yakun; Yang, K. (2018-10)
    For overbank flows in meandering channels, the flow direction along a meander varies and is affected by floodplain vegetation. This study proposes a model for predicting the depth-averaged two-dimensional flow direction (depth-averaged flow angle) along a meander in smooth and vegetated meandering compound channels. Laboratory experiments were performed in smooth and vegetated channels. Measurements show that the height of the secondary current cell in the main channel is increased by dense floodplain vegetation comparing with that in a non-vegetated channel. A method of determining the height of the cell is proposed. At the middle section between the apex and exit sections, where the secondary current cell is absent, the depth-averaged flow angle is independent of the height of the cell. Beyond the middle section, a new secondary current cell is formed, and the flow angle is highly dependent on the height of the cell. The proposed model is thoroughly verified using the flume experimental and field observed data. Good agreement is obtained between predictions and measurements, indicating that the proposed model is capable of accurately predicting the depth-averaged flow angle along a meander in smooth and vegetated meandering compound channels.
  • Parameter estimation of a six-lump kinetic model of an industrial fluid catalytic cracking unit

    John, Yakubu M.; Mustafa, M.A.; Patel, Rajnikant; Mujtaba, Iqbal M. (2018)
    In this work a simulation of detailed steady state model of an industrial fluid catalytic cracking (FCC) unit with a newly proposed six-lumped 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 kg-lump/kg-feed with a 0.81% error while gasoline as 0.4863 kg-lump/kg-feed 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 six-lump model as catalyst-to-oil (C/O) ratios were varied and the results predicted the typical riser profiles.
  • Nanoindentation analysis of oriented polypropylene: Influence of elastic properties in tension and compression

    Vgenopoulos, D.; Sweeney, John; Grant, C.A.; Thompson, Glen P.; Spencer, Paul E.; Caton-Rose, Philip D.; Coates, Philip D. (2018-08)
    Polypropylene has been oriented by solid-phase deformation processing to draw ratios up to ∼16, increasing tensile stiffness along the draw direction by factors up to 12. Nanoindentation of these materials showed that moduli obtained for indenter tip motion along the drawing direction (3) into to 1–2 plane (axial indentation) were up to 60% higher than for indenter tip motion along the 2 direction into the 1–3 plane (transverse indentation). In static tests, tensile and compressive determinations of elastic modulus gave results differing by factors up to ∼5 for strain along the draw direction. A material model incorporating both orthotropic elasticity and tension/compression asymmetry was developed for use with Finite Element simulations. Elastic constants for the oriented polypropylene were obtained by combining static testing and published ultrasonic data, and used as input for nanoindentation simulations that were quantitatively successful. The significance of the tension/compression asymmetry was demonstrated by comparing these predictions with those obtained using tensile data only, which gave predictions of indentation modulus higher by up to 70%.
  • Experimental study on the flexural behavior of ECC-concrete hybrid composite beams reinforced with FRP and steel bars

    Ge, W-J.; Ashour, Ashraf F.; Yu, J.; Gao, P.; Cao, D-F.; Cai, C.; Ji, X. (2018)
    This paper aims to investigate the flexural behavior of engineered cementitious composite (ECC)-concrete hybrid composite beams reinforced with fiber reinforced polymer (FRP) bars and steel bars. Thirty two hybrid reinforced composite beams having various ECC height replacement ratio and combinations of FRP and steel reinforcements were experimentally tested to failure in flexure. Test results showed that cracking, yield and ultimate moments as well as the stiffness of hybrid and ECC beams are improved compared with traditional concrete beams having the same reinforcement, owing to the excellent tensile properties of ECC materials. The average crack spacing and width decrease with the increase of ECC height replacement ratio. The ductility of hybrid reinforced composite beams is higher than that of traditional reinforced concrete beams while their practical reinforcement ratios are similar. Reinforced ECC beams show considerable energy dissipation capacity owing to ECC’s excellent deformation ability. Considering the constitutive models of materials, compatibility and equilibrium conditions, formulas for the prediction of cracking, yield and ultimate moments as well as deflections of hybrid reinforced ECC-concrete composite beams are developed. The proposed formulas are in good agreement with the experimental results. A comprehensive parametric analysis is, then, conducted to illustrate the effect of reinforcement, ECC and concrete properties on the moment capacity, curvature, ductility and energy dissipation of composite beams.

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