• Fabrication and characterizations of hydrogels for cartilage repair

      Kaur, Payal; Khaghani, Seyed A.; Oluwadamilola, Agbabiaka; Khurshid, Z.; Zafar, M.S.; Mozafari, M.; Youseffi, Mansour; Sefat, Farshid (2017-09-26)
      Articular cartilage is a vascular tissue with limited repair capabilities, leaving an afflicted person in extreme pain. The tissue experiences numerous forces throughout its lifetime. This study focuses on development of a novel hydrogel composed of chitosan and β-glycerophosphate for articular cartilage repair. The aim of this study was to investigate the mechanical properties and swelling behaviour of a novel hydrogel composed of chitosan and β-glycerophosphate for cartilage repair. The mechanical properties were measured for compression forces. Mach-1 mechanical testing system was used to obtain storage and loss modulus for each hydrogel sample to achieve viscoelastic properties of fabricated hydrogels. Two swelling tests were carried out to compare water retaining capabilities of the samples. The hydrogel samples were made of five different concentrations of β-glycerophosphate cross-linked with chitosan. Each sample with different β-glycerophosphate concentration underwent sinusoidal compression forces at three different frequencies -0.1Hz, 0.316Hz and 1Hz. The result of mechanical testing was obtained as storage and loss modulus. Storage modulus represents the elastic component and loss modulus represents the viscosity of the samples. The results obtained for 1Hz were of interest because the knee experiences frequency of 1Hz during walking.
    • Fabrication and evaluation of electrospun PCL-gelatin micro-/nanofiber membranes for anti-infective GTR implants

      Xue, J.; He, M.; Liang, Y.; Crawford, A.; Coates, Philip D.; Chen, D.; Shi, R.; Zhang, L. (2014)
    • Facial age synthesis using sparse partial least squares (the case of Ben Needham)

      Bukar, Ali M.; Ugail, Hassan (2017-09)
      Automatic facial age progression (AFAP) has been an active area of research in recent years. This is due to its numerous applications which include searching for missing. This study presents a new method of AFAP. Here, we use an Active Appearance Model (AAM) to extract facial features from available images. An ageing function is then modelled using Sparse Partial Least Squares Regression (sPLS). Thereafter, the ageing function is used to render new faces at different ages. To test the accuracy of our algorithm, extensive evaluation is conducted using a database of 500 face images with known ages. Furthermore, the algorithm is used to progress Ben Needham’s facial image that was taken when he was 21 months old to the ages of 6, 14 and 22 years. The algorithm presented in this paper could potentially be used to enhance the search for missing people worldwide.
    • Facial Analysis for Real-Time Application: A Review in Visual Cues Detection Techniques

      Yap, Moi Hoon; Ugail, Hassan; Zwiggelaar, R. (2012-11-30)
      Emerging applications in surveillance, the entertainment industry and other human computer interaction applications have motivated the development of real-time facial analysis research covering detection, tracking and recognition. In this paper, the authors present a review of recent facial analysis for real-time applications, by providing an up-to-date review of research efforts in human computing techniques in the visible domain. The main goal is to provide a comprehensive reference source for researchers, regardless of specific research areas, involved in real-time facial analysis. First, the authors undertake a thorough survey and comparison in face detection techniques. In this survey, they discuss some prominent face detection methods presented in the literature. The performance of the techniques is evaluated by using benchmark databases. Subsequently, the authors provide an overview of the state-of-the-art of facial expressions analysis and the importance of psychology inherent in facial expression analysis. During the last decades, facial expressions analysis has slowly evolved into automatic facial expressions analysis due to the popularity of digital media and the maturity of computer vision. Hence, the authors review some existing automatic facial expressions analysis techniques. Finally, the authors provide an exemplar for the development of a facial analysis real-time application and propose a model for facial analysis. This review shows that facial analysis for real-time application involves multi-disciplinary aspects and it is important to take all domains into account when building a reliable system.
    • Facial Behavioral Analysis: A Case Study in Deception Detection

      Yap, Moi Hoon; Ugail, Hassan; Zwiggelaar, R. (2014-02-05)
      The objective of every wind energy producer is to reduce operational costs associated to the production as a way to increase profits. One other issue that must be looked carefully is the equipment maintenance. Increase the availability of wind turbines by reducing the downtime associated to failures is a good strategy to achieve the main goal of increase profits. As a way to help in the definition of the best maintenance strategies, condition monitoring systems (CMS) have an important role to play. Informatics tools to make the condition monitoring of the wind turbines were developed and are now being installed as a way to help producers reducing the operational costs. There are a lot of developed systems to do the monitoring of a wind turbine or the whole wind park, in this paper will be made an overview of the most important systems.
    • Facial Geometry Parameterisation based on Partial Differential Equations

      Sheng, Y.; Gonzalez Castro, Gabriela; Ugail, Hassan; Willis, P. (2011)
      Geometric modelling using Partial Differential Equations (PDEs) has been gradually recognised due to its smooth instinct, as well as the ability to generate a variety of geometric shapes by intuitively manipulating a relatively small set of PDE boundary curves. In this paper we explore and demonstrate the feasibility of the PDE method in facial geometry parameterisation. The geometry of a generic face is approximated by evaluating spectral solutions to a group of fourth order elliptic PDEs. Our PDE-based parameterisation scheme can produce and animate a high-resolution 3D face with a relatively small number of parameters. By taking advantage of parametric representation, the PDE method can use one fixed animation scheme to manipulate the facial geometry in varying Levels of Detail (LODs), without any further process.
    • Factorization in finite quantum systems.

      Vourdas, Apostolos (2003)
      Unitary transformations in an angular momentum Hilbert space H(2j + 1), are considered. They are expressed as a finite sum of the displacement operators (which play the role of SU(2j + 1) generators) with the Weyl function as coefficients. The Chinese remainder theorem is used to factorize large qudits in the Hilbert space H(2j + 1) in terms of smaller qudits in Hilbert spaces H(2ji + 1). All unitary transformations on large qudits can be performed through appropriate unitary transformations on the smaller qudits.
    • Factors affecting tranquillity in the countryside.

      Watts, Gregory R.; Pheasant, Robert J. (24/05/2013)
      Previous work on elucidating the tranquillity of various environments has largely focussed on prediction and validation in urban environments. The setting for the latest phase of research was an English country park and surrounding moors on the urban fringe located 8 miles west of Bradford. Within the area selected there were a number of environments and man-made features and sounds that were thought to significantly affect tranquillity and which were not covered in earlier studies. The experiment extended over a number of months and utilised a jury technique for evaluation involving leading small groups of walkers to different locations in quasi-random order. At each location participants were asked to complete a short questionnaire and measurements of the physical soundscape and landscape images were used to interpret the results and give insights into the importance of the various factors affecting tranquillity. Such data will be useful for effective environmental management and conservation in the countryside.
    • Fail Over Strategy for Fault Tolerance in Cloud Computing Environment

      Mohammed, Bashir; Kiran, Mariam; Maiyama, Kabiru M.; Kamala, Mumtaz A.; Awan, Irfan U. (2017-09)
      Cloud fault tolerance is an important issue in cloud computing platforms and applications. In the event of an unexpected system failure or malfunction, a robust fault-tolerant design may allow the cloud to continue functioning correctly possibly at a reduced level instead of failing completely. To ensure high availability of critical cloud services, the application execution and hardware performance, various fault tolerant techniques exist for building self-autonomous cloud systems. In comparison to current approaches, this paper proposes a more robust and reliable architecture using optimal checkpointing strategy to ensure high system availability and reduced system task service finish time. Using pass rates and virtualised mechanisms, the proposed Smart Failover Strategy (SFS) scheme uses components such as Cloud fault manager, Cloud controller, Cloud load balancer and a selection mechanism, providing fault tolerance via redundancy, optimized selection and checkpointing. In our approach, the Cloud fault manager repairs faults generated before the task time deadline is reached, blocking unrecoverable faulty nodes as well as their virtual nodes. This scheme is also able to remove temporary software faults from recoverable faulty nodes, thereby making them available for future request. We argue that the proposed SFS algorithm makes the system highly fault tolerant by considering forward and backward recovery using diverse software tools. Compared to existing approaches, preliminary experiment of the SFS algorithm indicate an increase in pass rates and a consequent decrease in failure rates, showing an overall good performance in task allocations. We present these results using experimental validation tools with comparison to other techniques, laying a foundation for a fully fault tolerant IaaS Cloud environment.
    • Failure Analysis Modelling in an Infrastructure as a Service (Iaas) Environment

      Mohammed, Bashir; Modu, Babagana; Maiyama, Kabiru M.; Ugail, Hassan; Awan, Irfan U.; Kiran, Mariam (2018)
      Failure Prediction has long known to be a challenging problem. With the evolving trend of technology and growing complexity of high-performance cloud data centre infrastructure, focusing on failure becomes very vital particularly when designing systems for the next generation. The traditional runtime fault-tolerance (FT) techniques such as data replication and periodic check-pointing are not very effective to handle the current state of the art emerging computing systems. This has necessitated the urgent need for a robust system with an in-depth understanding of system and component failures as well as the ability to predict accurate potential future system failures. In this paper, we studied data in-production-faults recorded within a five years period from the National Energy Research Scientific computing centre (NERSC). Using the data collected from the Computer Failure Data Repository (CFDR), we developed an effective failure prediction model focusing on high-performance cloud data centre infrastructure. Using the Auto-Regressive Moving Average (ARMA), our model was able to predict potential future failures in the system. Our results also show a failure prediction accuracy of 95%, which is good.
    • Failure Prediction using Machine Learning in a Virtualised HPC System and application

      Bashir, Mohammed; Awan, Irfan U.; Ugail, Hassan; Muhammad, Y. (2019-06)
      Failure is an increasingly important issue in high performance computing and cloud systems. As large-scale systems continue to grow in scale and complexity, mitigating the impact of failure and providing accurate predictions with sufficient lead time remains a challenging research problem. Traditional existing fault-tolerance strategies such as regular check-pointing and replication are not adequate because of the emerging complexities of high performance computing systems. This necessitates the importance of having an effective as well as proactive failure management approach in place aimed at minimizing the effect of failure within the system. With the advent of machine learning techniques, the ability to learn from past information to predict future pattern of behaviours makes it possible to predict potential system failure more accurately. Thus, in this paper, we explore the predictive abilities of machine learning by applying a number of algorithms to improve the accuracy of failure prediction. We have developed a failure prediction model using time series and machine learning, and performed comparison based tests on the prediction accuracy. The primary algorithms we considered are the Support Vector Machine (SVM), Random Forest(RF), k-Nearest Neighbors (KNN), Classi cation and Regression Trees (CART) and Linear Discriminant Analysis (LDA). Experimental results indicates that the average prediction accuracy of our model using SVM when predicting failure is 90% accurate and effective compared to other algorithms. This f inding implies that our method can effectively predict all possible future system and application failures within the system.
    • Fall detection system for elderly using Arduino, Gyroscope and GPS Module

      Fitriawan, H.; Susanto, Misfa; Santoso, M.R.F.; Purwiyanti, S.; Hu, Yim Fun; Sigwele, Tshiamo (2018)
    • 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.
    • Fast mapping of finite element field variables between meshes with different densities and element types

      Scrimieri, Daniele; Afazov, S.M.; Becker, A.A.; Ratchev, S.M. (2014-01)
      In the simulation of a chain of manufacturing processes, several finite element packages can be employed and for each process or package a different mesh density or element type may be the most suitable. Therefore, there is a need for transferring finite element analysis (FEA) data among packages and mapping it between meshes. This paper presents efficient algorithms for mapping FEA data between meshes with different densities and element types. An in-core spatial index is created on the mesh from which FEA data is transferred. The index is represented by a dynamic grid partitioning the underlying space from which nodes and elements are drawn into equal-sized cells. Buckets containing references to the nodes indexed are associated with the cells in a many-to-one correspondence. Such an index makes nearest neighbour searches of nodes and elements much faster than sequential scans. An experimental evaluation of the mapping techniques using the index is conducted. The algorithms have been implemented in the open source finite element data exchange system FEDES.
    • Faster visual reaction times in elite athletes are not linked to better gaze stability

      Barrett, Brendan T.; Cruickshank, Alice G.; Flavell, J.C.; Bennett, S.J.; Buckley, John G.; Harris, J.M.; Scally, Andy J. (2020-08)
      The issue of whether visually-mediated, simple reaction time (VRT) is faster in elite athletes is contentious. Here, we examined if and how VRT is afected by gaze stability in groups of international cricketers (16 females, 28 males), professional rugby-league players (21 males), and non-sporting controls (20 females, 30 males). VRT was recorded via a button-press response to the sudden appearance of a stimulus (circular target—diameter 0.8°), that was presented centrally, or 7.5° to the left or right of fxation. The incidence and timing of saccades and blinks occurring from 450 ms before stimulus onset to 225 ms after onset were measured to quantify gaze stability. Our results show that (1) cricketers have faster VRT than controls; (2) blinks and, in particular, saccades are associated with slower VRT regardless of the level of sporting ability; (3) elite female cricketers had steadier gaze (fewer saccades and blinks) compared to female controls; (4) when we accounted for the presence of blinks and saccades, our group comparisons of VRT were virtually unchanged. The stability of gaze is not a factor that explains the difference between elite and control groups in VRT. Thus we conclude that better gaze stability cannot explain faster VRT in elite sports players.
    • Fault Detection of Brahmanbaria Gas Plant using Neural Network

      Sowgath, Md Tanvir; Ahmed, S. (2014-12-22)
      In recent years, several accidents in pioneer gas processing industries led industries to put emphasis on real-time fault detection. Neural Network (NN) based fault (abnormal situation) detection technique played an important role in monitoring industrial safety. In this work, an attempt has been made to study the fault detection of Brahmanbaria gas processing plant using multi layered feed forward NN based system. NN based fault detection system is trained, validated and tested using data generated using the dynamic model. Preliminary results show that NN based method is able to detect the faults of Brahmanbaria Gas processing plant for fewer no of faults.
    • Feasibility of Integrated Batch Reactive Distillation Columns for the Optimal Synthesis of Ethyl Benzoate

      Aqar, D.Y.; Rahmanian, Nejat; Mujtaba, Iqbal M. (2017-12-08)
      The synthesis of ethyl benzoate (EtBZ) via esterification of benzoic acid (BeZ) with ethanol in a reactive distillation is challenging due to complex thermodynamic behaviour of the chemical reaction and the difficulty of keeping the reactants together in the reaction zone (ethanol having the lowest boiling point can separate from the BeZ as the distillation proceeds) causing a significant decrease in the conversion of BeZ in a conventional reactive distillation column (batch or continuous). This might be the reason of not reporting the use of reactive distillation for EtBZ synthesis although the study of BeZ esterification reaction is available in the public literature. Our recently developed Integrated Conventional Batch Distillation (i-CBD) column offers the prospect of revisiting such reactions for the synthesis of EtBZ, which is the focus of this work. Clearly, i-CBD column outperforms the Conventional Batch Distillation (CBD) column in terms of product amount, purity and conversion of BeZ and eliminates the requirement of excess use of ethanol. For example, compared with CBD column, the i-CBD operation can yield EtBZ at a much higher purity (0.925 compared to 0.730) and can convert more benzoic acid (93.57% as opposed to only 74.38%).
    • Feasibility of novel integrated dividing-wall batch reactive distillation processes for the synthesis of methyl decanoate

      Aqar, D.Y.; Rahmanian, Nejat; Mujtaba, Iqbal M. (2018-08-31)
      The production of methyl decanoate (MeDC) through esterification of decanoic acid (DeC) with methanol by reactive distillation is operationally challenging and energy-intensive due to the complicated behaviour of the reaction system and the difficulty of retaining the reactants together in the reaction region. Methanol being the lightest component in the mixture can separate itself from the reactant DeC as the distillation proceeds which will cause a massive reduction in the conversion of DeC utilizing either a batch or continuous distillation process. Aiming to overcome this type of the potential problem, novel integrated divided-wall batch reactive distillation configuration (i-DWBD) with recycling from the distillate tank is established in this study and is examined in detail. This study has clearly demonstrated that the integrated divided-wall batch reactive distillation column (i-DWBD) is superior to the traditional conventional batch distillation (CBD) and both the divided-wall (DWBD), and split reflux divided-wall (sr-DWBD) batch reactive distillation configurations in terms of maximum achievable purity of MeDC and higher conversion of DeC into MeDC. In addition, significant batch time and energy savings are possible when the i-DWBD is operated in multi-reflux mode.
    • A Feasibility Study of BBP for predicting shear capacity of FRP reinforced concrete beams without stirrups.

      Golafshani, E.M.; Ashour, Ashraf F.
      Shear failure of concrete elements reinforced with Fiber Reinforced Polymer (FRP) bars is generally brittle, requiring accurate predictions to avoid it. In the last decade, a variety of artificial intelligence based approaches have been successfully applied to predict the shear capacity of FRP Reinforced Concrete (FRP-RC). In this paper, a new approach, namely, biogeography-based programming (BBP) is introduced for predicting the shear capacity of FRP-RC beams based on test results available in the literature. The performance of the BBP model is compared with several shear design equations, two previously developed artificial intelligence models and experimental results. It was found that the proposed model provides the most accurate results in calculating the shear capacity of FRP-RC beams among the considered shear capacity models. The proposed BBP model can also correctly predict the trend of different influencing variables on the shear capacity of FRP-RC beams.