• A machine learning approach for ethnic classification: the British Pakistani face

      Khalid Jilani, Shelina; Ugail, Hassan; Bukar, Ali M.; Logan, Andrew J.; Munshi, Tasnim (2017)
      Ethnicity is one of the most salient clues to face identity. Analysis of ethnicity-specific facial data is a challenging problem and predominantly carried out using computer-based algorithms. Current published literature focusses on the use of frontal face images. We addressed the challenge of binary (British Pakistani or other ethnicity) ethnicity classification using profile facial images. The proposed framework is based on the extraction of geometric features using 10 anthropometric facial landmarks, within a purpose-built, novel database of 135 multi-ethnic and multi-racial subjects and a total of 675 face images. Image dimensionality was reduced using Principle Component Analysis and Partial Least Square Regression. Classification was performed using Linear Support Vector Machine. The results of this framework are promising with 71.11% ethnic classification accuracy using a PCA algorithm + SVM as a classifier, and 76.03% using PLS algorithm + SVM as a classifier.
    • Machine Learning for Botnet Detection: An Optimized Feature Selection Approach

      Lefoane, Moemedi; Ghafir, Ibrahim; Kabir, Sohag; Awan, Irfan U. (2021-12)
      Technological advancements have been evolving for so long, particularly Internet of Things (IoT) technology that has seen an increase in the number of connected devices surpass non IoT connections. It has unlocked a lot of potential across different organisational settings from healthcare, transportation, smart cities etc. Unfortunately, these advancements also mean that cybercriminals are constantly seeking new ways of exploiting vulnerabilities for malicious and illegal activities. IoT is a technology that presents a golden opportunity for botnet attacks that take advantage of a large number of IoT devices and use them to launch more powerful and sophisticated attacks such as Distributed Denial of Service (DDoS) attacks. This calls for more research geared towards the detection and mitigation of botnet attacks in IoT systems. This paper proposes a feature selection approach that identifies and removes less influential features as part of botnet attack detection method. The feature selection is based on the frequency of occurrence of the value counts in each of the features with respect to total instances. The effectiveness of the proposed approach is tested and evaluated on a standard IoT dataset. The results reveal that the proposed feature selection approach has improved the performance of the botnet attack detection method, in terms of True Positive Rate (TPR) and False Positive Rate (FPR). The proposed methodology provides 100% TPR, 0% FPR and 99.9976% F-score.
    • Machine learning-based investigation of the association between CMEs and filaments

      Al-Omari, M.; Qahwaji, Rami S.R.; Colak, Tufan; Ipson, Stanley S. (2010-04)
      In this work we study the association between eruptive filaments/prominences and coronal mass ejections (CMEs) using machine learning-based algorithms that analyse the solar data available between January 1996 and December 2001. The Support Vector Machine (SVM) learning algorithm is used for the purpose of knowledge extraction from the association results. The aim is to identify patterns of associations that can be represented using SVM learning rules for the subsequent use in near real-time and reliable CME prediction systems. Timing and location data in the NGDC filament catalogue and the SOHO/LASCO CME catalogue are processed to associate filaments with CMEs. In the previous studies which classified CMEs into gradual and impulsive CMEs, the associations were refined based on CME speed and acceleration. Then the associated pairs were refined manually to increase the accuracy of the training dataset. In the current study, a data- mining system has been created to process and associate filament and CME data, which are arranged in numerical training vectors. Then the data are fed to SVMs to extract the embedded knowledge and provide the learning rules that could have the potential, in the future, to provide automated predictions of CMEs. The features representing the event time (average of the start and end times), duration, type and extent of the filaments are extracted from all the associated and not-associated filaments and converted to a numerical format that is suitable for SVM use. Several validation and verification methods are used on the extracted dataset to determine if CMEs can be predicted solely and efficiently based on the associated filaments. More than 14000 experiments are carried out to optimise the SVM and determine the input features that provide the best performance.
    • Maintaining QoS through preferential treatment to UMTS services

      Awan, Irfan U.; Al-Begain, Khalid (2003)
      One of the main features of the third generation (3G) mobile networks is their capability to provide different classes of services; especially multimedia and real-time services in addition to the traditional telephony and data services. These new services, however, will require higher Quality of Service (QoS) constraints on the network mainly regarding delay, delay variation and packet loss. Additionally, the overall traffic profile in both the air interface and inside the network will be rather different than used to be in today's mobile networks. Therefore, providing QoS for the new services will require more than what a call admission control algorithm can achieve at the border of the network, but also continuous buffer control in both the wireless and the fixed part of the network to ensure that higher priority traffic is treated in the proper way. This paper proposes and analytically evaluates a buffer management scheme that is based on multi-level priority and Complete Buffer Sharing (CBS) policy for all buffers at the border and inside the wireless network. The analytical model is based on the G/G/1/N censored queue with single server and R (R¿2) priority classes under the Head of Line (HoL) service rule for the CBS scheme. The traffic is modelled using the Generalised Exponential distribution. The paper presents an analytical solution based on the approximation using the Maximum Entropy (ME) principle. The numerical results show the capability of the buffer management scheme to provide higher QoS for the higher priority service classes.
    • Maintenance cost models in deregulated power systems under opportunity costs.

      Al-Arfaj, Khalid A.; Dahal, Keshav P.; Azaiez, M.N. (2007)
      Maintenance costs in deregulated power systems play an important role. This mainly includes direct costs associated with material and labor costs; and indirect costs associated with spare parts inventory, shipment, test equipment cost, indirect labor, and opportunity costs. The cost function is used as the sole or main component of the objective function in maintenance scheduling and planning activities. The cost has been modeled in literature with several representations for centralized power systems. With deregulation of power industries in many countries the costs representation to be used within the maintenance model in the decentralized power systems has become an important research question. This paper presents modeling of different components of maintenance costs that can be used within the main objective function of the maintenance scheduling and planning problem for the deregulated environment.
    • Maintenance scheduling for railway tracks under limited possession time

      Dao, Cuong D.; Basten, R.; Hartmann, A. (2018-08)
      Maintenance planning for busy railway systems is challenging because there is growing pressure on increasing operation time, which reduces the infrastructure-accessible time for maintenance. This paper proposes an optimization model that is aimed at finding the best maintenance schedule for multiple components in a railway track to minimize the total cost in the planning horizon. One distinct and practical feature of the model is that the track accessible time for maintenance is limited. We formulate all relevant costs in the component's life cycle, including maintenance cost, fixed track-closure (possession) cost, social-economic cost related to the effects of maintenance time on the train operation, and service-life shortening cost due to the shifting of activities. Generally, it is beneficial to cluster and maintain several components in a single possession because this helps reduce the cost by occupying the track only once. However, the decision must depend on the available possession time. A sensitivity analysis is performed to highlight the effects of available possession time on the number of required possessions as well as the total cost incurred.
    • Maintenance Scheduling With Delay-time Modelling - An Overview

      Du, Jing-Yu; Li, Jian-Ping; Hu, Yim Fun; Guan, X.; Si, M.; Liu, B. (2021-09-01)
      Effective maintenance is a key for infrastructures’ high operational reliability. The integration of corrective repairs and schedule-based failure preventions has been a mainstream of modern maintenance, and an associated policy-making technique, delay-time modelling, is overviewed in this paper for optimising the maintenance cost-efficiency in different practical scenarios, including imperfect, opportunistic and nested maintenance. A few typical examples of its applications in minimising maintenance operating expenses are discussed in this paper and their results are explained to better demonstrate the benefits of the technique. This work aims to prepare for the future applications of the delay-time modelling in railway maintenance policy making.
    • Making Asset Investment Decisions for Wastewater Systems That Include Sustainability

      Ashley, R.M.; Blackwood, D.; Butler, D.; Jowitt, P.; Davies, J.; Smith, H.; Gilmour, D.; Oltean-Dumbrava, Crina (2008-03)
      Effective integrated water management is a key component of the World Water Vision and the way in which aspirations for water equity may be realized. Part of the vision includes the promotion of sustainability of water systems and full accountability for their interaction with other urban systems. One major problem is that “sustainability” remains an elusive concept, although those involved with the provision of urban wastewater systems now recognize that decisions involving asset investment should use the “triple bottom line” approach to society, the economy, and the environment. The Sustainable Water Industry Asset Resource Decisions project has devised a flexible and adaptable framework of decision support processes that can be used to include the principles of sustainability more effectively. Decision mapping conducted at the outset of the project has shown that only a narrow range of criteria currently influence the outcome of asset investment decisions. This paper addresses the concepts of sustainability assessment and presents two case studies that illustrate how multicriteria decision support systems can enhance the assessment of the relative sustainability of a range of options when decisions are being made about wastewater asset investment.
    • Making use of turbulence and its interaction with sound: a non-invasive flow monitor

      Nichols, Andrew; Horoshenkov, Kirill V.; Tait, Simon J.; Shepherd, Simon J. (2014)
      A novel acoustic sensor has been developed which is capable of remotely monitoring the free surface ‘fingerprint’ of shallow flows. The temporal and spatial properties of this fingerprint are shown to contain a wealth of information regarding the nature of the flow itself. The remote measurement can thereby be used to infer the bulk flow properties such as depth, velocity, and hydraulic roughness to within 8 % accuracy. The instrument is totally non-invasive and as such is low cost, low maintenance, and low power. Such a device will allow for widespread monitoring of flow conditions in drainage and river networks, informing flood models, and facilitating pro-active maintenance and real time control.
    • Malware Propagation Modelling in Peer-to-Peer Networks: A Review

      Musa, Ahmad S.; Al-Mohannadi, Hamad; Alhamar, J. (2018)
      Peer-to-Peer (P2P) network is increasingly becoming the most important means of trading content throughout the last years due to the constant evolvement of the cyber world. This popularity made the P2P network susceptible to the spread of malware. The detection of the cause of malware propagation is now critical to the survival of P2P networks. This paper offers a review of the current relevant mathematical propagation models that have been proposed to date to predict the propagation behavior of a malware in a P2P network. We analyzed the models proposed by researchers and experts in the field by evaluating their limitations and a possible alternative for improving the analysis of the expected behavior of a malware spread.
    • The Man Who Killed Suzy Lamplugh.

      Rashid, M. Ali; Entwhistle, C.; Jones, S. (2002)
      A reinvestigation into the unsolved murder of 25-year-old estate agent Suzy Lamplugh who went missing in 1986. Despite appeals on 'Crimewatch' and four separate investigations her killer was never found. Documentary profiles John Cannan, currently serving three life sentences for robbery, rape and murder, and who senior police officers believe to be the estate agents murderer.
    • Manipulation of PDE surfaces using an interactively defined parameterisation

      Ugail, Hassan; Bloor, M.I.G.; Wilson, M.J. (Elsevier, 1999)
      Manipulation of PDE surfaces using a set of interactively defined parameters is considered. The PDE method treats surface design as a boundary-value problem and ensures that surfaces can be defined using an appropriately chosen set of boundary conditions and design parameters. Here we show how the data input to the system, from a user interface such as the mouse of a computer terminal, can be efficiently used to define a set of parameters with which to manipulate the surface interactively in real time.
    • Marginal cost analysis of single-item maintenance policies with several decision variables

      Csenki, Attila (2004)
      The marginal cost approach for the analysis of repair/replacement models was introduced by Berg in 1980 and has since been applied to many maintenance policies of various complexity. All models hitherto analysed in the literature by the marginal cost approach have one single decision variable only, this being, typically, the age of the current item at the time of ordering or replacement. This paper is concerned with the extension of the marginal cost technique to maintenance policies with several decision variables. After addressing the general framework appropriate for the multi-parameter case, we exemplify the workings of the technique by analysing a two-variable maintenance model involving replacement and minimal repair. We demonstrate that the marginal cost approach is an attractive and intuitively appealing technique also for models with several decision variables. Just as in the single-parameter situation, the approach is amenable to economic interpretation, a welcome feature for users of maintenance models with a prime interest in its economic (rather than its mathematical) aspects. As an added bonus of the marginal cost approach, in our example, some otherwise necessary tools from the theory of stochastic processes are dispensable.
    • Markov chains with doubly stochastic transition matrices and application to a sequence of non-selective quantum measurements

      Vourdas, Apostolos (2022-05)
      A time-dependent finite-state Markov chain that uses doubly stochastic transition matrices, is considered. Entropic quantities that describe the randomness of the probability vectors, and also the randomness of the discrete paths, are studied. Universal convex polytopes are introduced which contain all future probability vectors, and which are based on the Birkhoff–von Neumann expansion for doubly stochastic matrices. They are universal in the sense that they depend only on the present probability vector, and are independent of the doubly stochastic transition matrices that describe time evolution in the future. It is shown that as the discrete time increases these convex polytopes shrink, and the minimum entropy of the probability vectors in them increases. These ideas are applied to a sequence of non-selective measurements (with different projectors in each step) on a quantum system with -dimensional Hilbert space. The unitary time evolution in the intervals between the measurements, is taken into account. The non-selective measurements destroy stroboscopically the non-diagonal elements in the density matrix. This ‘hermaphrodite’ system is an interesting combination of a classical probabilistic system (immediately after the measurements) and a quantum system (in the intervals between the measurements). Various examples are discussed. In the ergodic example, the system follows asymptotically all discrete paths with the same probability. In the example of rapidly repeated non-selective measurements, we get the well known quantum Zeno effect with ‘frozen discrete paths’ (presented here as a biproduct of our general methodology based on Markov chains with doubly stochastic transition matrices).
    • Mastering continuous improvement (CI): the roles and competences of mid-level management and their impact on the organisation’s CI capability

      Fannon, S.R.; Munive-Hernandez, J. Eduardo; Campean, I. Felician (2022-01-18)
      Purpose – This paper establishes a comprehensive basis for understanding the roles and competences of midlevel management and their influence on the effectiveness of continuous improvement (CI) capability within an organisation. Design/methodology/approach – This research builds upon the hypothesis that methods alone do not lead to successful CI capability development. It focuses on the role of mid-level management in driving a CI environment that underpins the effectiveness of CI capability. A reference model for the CI environment is synthesised based on critical literature review, integrating CI culture, CI enablers and CI leadership elements.A comprehensive framework is introduced to define CI leadership roles and competence indicators. A quantitative benchmarking study involving structured interviews with 15 UK organisations was undertaken to collect evidence for a causal relationship between CI leadership competences and CI capability. Findings – Analysis of the benchmarking data provides clear evidence of the causal relationship between the CI leadership competences of mid-level management and CI capability of the organisation. Given that the empirical study was structured on the basis of the CI leadership roles and competences framework introduced in this paper, this also provides validation for the proposed framework and the CI environment model. Practical implications – The evidence-based knowledge of the positive relationship between the midmanagement CI leadership competences and the effectiveness of the CI capability informs strategic organisational development interventions towards enhancing CI capability and effectiveness, ultimately underpinning productivity enhancement and sustainability. The framework for mid-level management CI leadership roles, responsibilities and competences introduced in this paper and grounded in underpinning work undertaken within a large automotive Original Equipment Manufacturer (OEM), can be adapted by any organisation. The CI environment reference model should provide a comprehensive support for strategists to communicate the framework for CI capability improvement within an organisation, to enhance acceptability and adherence to improvement actions. Originality/value – This research proves for the first time the significance of the causal relationship between the CI leadership competences and the effectiveness of the CI capability within an organisation, thus filling an important gap between established previous work, focussing on the role of mid-level management on one side and practitioner and team level roles, methodologies and tools. The proposed CI environment model is a theoretical contribution with reference value for both practice and further studies. The comprehensive framework for mid-level management CI leadership roles, responsibilities and competences introduced in this paper provides sound foundation to deliver CI leadership in the workplace.
    • A material model for multiaxial stretching and stress relaxation of polypropylene under process conditions

      Sweeney, John; O'Connor, C.P.J.; Spencer, Paul E.; Pua, H.; Caton-Rose, Philip D.; Martin, P.J. (2012-11)
      Polypropylene sheets have been stretched at 160 °C to a state of large biaxial strain of extension ratio 3, and the stresses then allowed to relax at constant strain. The state of strain is reached via a path consisting of two sequential planar extensions, the second perpendicular to the first, under plane stress conditions with zero stress acting normal to the sheet. This strain path is highly relevant to solid phase deformation processes such as stretch blow moulding and thermoforming, and also reveals fundamental aspects of the flow rule required in the constitutive behaviour of the material. The rate of decay of stress is rapid, and such as to be highly significant in the modelling of processes that include stages of constant strain. A constitutive equation is developed that includes Eyring processes to model both the stress relaxation and strain rate dependence of the stress. The axial and transverse stresses observed during loading show that the use of a conventional Levy-Mises flow rule is ineffective, and instead a flow rule is used that takes account of the anisotropic state of the material via a power law function of the principal extension ratios. Finally the constitutive model is demonstrated to give quantitatively useful representation of the stresses both in loading and in stress relaxation.
    • Mathematical model for calibration of nonlinear responses in biological media exposed to RF energy

      See, Chan H.; Abd-Alhameed, Raed A.; Excell, Peter S. (2014)
      This paper presents a circuit model which is used to calibrate the performance of nonlinear RF energy conversion inside a high quality factor resonant cavity with a known nonlinear loading device. The nonlinear radiofrequency energy conversion can be detected by exciting the fundamental operating frequency and observing the second harmonic resonant frequency within a doubly resonant cavity. By implementing the proposed mathematical model, the required input power can be estimated to maximise the chance of detecting the weak second harmonic signal prior to carry out the measurement.
    • Mathematical Model for Calibration of Potential Detection of Nonlinear Responses in Biological Media Exposed to RF Energy

      See, Chan H.; Abd-Alhameed, Raed A.; Mirza, Ahmed F.; McEwan, Neil J.; Excell, Peter S.; Balzano, Q. (2017-01-10)
      An efficient way to test for potential unsymmetrical nonlinear responses in biological tissue samples exposed to a microwave signal is to observe the second harmonic in a cavity resonant at the two frequencies, with collocated antinodes. Such a response would be of interest as being a mechanism that could enable demodulation of information-carrying waveforms. In this work, an electric circuit model is proposed to facilitate calibration of any putative nonlinear RF energy conversion inside a high quality-factor resonant cavity with a known nonlinear loading device. The first and second harmonic responses of the cavity due to loading with the nonlinear and lossy material are also demonstrated. The results from the proposed mathematical model give a good indication of the input power required to detect any very weak second harmonic signal in relation to the sensitivity of the measurement equipment. Hence, this proposed mathematical model will assist in determining the level of the second harmonic signal in the detector as a function of the specific input power applied.
    • Mathematical modeling of association attempt with the base station for maximum number of customer premise equipments in the IEEE 802.22 network

      Afzal, Humaira; Awan, Irfan U.; Mufti, Muhammad R. (2015)
      Abstract: Avoiding collision among contending customer premise equipments (CPEs) attempting to associate with a base station (BS), the only available solution in IEEE 802.22 standard is binary exponential random backoff process in which the contending CPEs retransmit their association requests. The number of attempts the CPEs sends their requests to the BS are fixed in IEEE 802.22 network. This paper presents a mathematical framework for helping the BS in determining at which attempt the majority of the CPEs become the part of wireless regional area network (WRAN) from a particular number of contending CPEs at a given initial contention window size.
    • Mathematical modelling and numerical simulation of CO2/CH4 separation in a polymeric membrane

      Gilassi, S.; Rahmanian, Nejat (2015-11-01)
      CO2 capture from natural gas was experimentally and theoretically studied using a dead-end polymeric permeation cell. A numerical model was proposed for the separation of CO2/CH4 using Polytetrafluoroethylene (PTFE) in a flat sheet membrane module and developed based upon the continuity, momentum and mass transfer equations. The slip velocity condition was considered to show the reflection of gas flow in contact with the membrane surface. The solution method was based on the well-known SIMPLE algorithm and implemented using MATLAB to determine the velocity and concentration profiles. Due to change in velocity direction in the membrane module, the hybrid differencing scheme was used to solve the diffusion-convection equation. The results of the model were compared with the experimental data obtained as part of this work and good agreement was observed. The distribution of CO2 concentration inside the feed and permeate chambers was shown and the velocity profile at the membrane surface was also determined using reflection factor for polymericmembrane. The modelling result revealed that increasing the amount of CO2 in gas feed resulted in an increase in the CO2 in the permeate stream while the gas feed pressure increased. By changing the permeability, the model developed by use of the solution-diffusion concept could be used for all polymeric membranes with flat sheet modules.