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  • Environment driven consumer EC model incorporating complexities of consumer body dynamics

    Ali, S.M.; Khan, B.; Mokryani, Geev; Mehmood, C.A.; Jawad, M.; Farid, U. (2019)
    Energy consumption (EC) of consumers primarily depends on comfort level (CL) affirmed by brain sensations of the central nervous system. Environmental parameters such as surroundings, relative humidity, air temperature, solar irradiance, air pressure, and cloud cover directly influence consumer body temperature that in return affect blood dynamics perturbing brain comfort sensations. This CL (either in summer, winter, autumn, or spring season) is a function of external environment and internal body variations that force a consumer toward EC. To develop a new concept of consumer's EC, first the authors described environment parameters in detail with relation to surroundings and EC. Considering this, they tabulated a generic relation of consumer's CL with EC and environment temperature. Second, to build an inter-related bond between the environmental effects on consumer body dynamics, they analysed theoretically and mathematically above mutual relations between medical and environmental sciences. Finally, they present their conceptual EC model based on a closed-loop feedback system. This model is a complex non-linear adaptive system with environmental and surrounding parameters as input to the system resulting in an optimised EC, considering consumer CL as a key parameter for the system.
  • Super-Wide Impedance Bandwidth Planar Antenna for Microwave and Millimeter-Wave Applications

    Alibakhshikenari, M.; Virdee, B.S.; See, C.H.; Abd-Alhameed, Raed A.; Falcone, F.; Limiti, E. (2019-05-19)
    A feasibility study of a novel configuration for a super-wide impedance planar antenna is presented based on a 2 × 2 microstrip patch antenna (MPA) using CST Microwave Studio. The antenna comprises a symmetrical arrangement of four-square patches that are interconnected to each other with cross-shaped high impedance microstrip lines. The antenna array is excited through a single feedline connected to one of the patches. The proposed antenna array configuration overcomes the main drawback of conventional MPA with a narrow bandwidth that is typically <5%. The antenna exhibits a super-wide frequency bandwidth from 20 GHz to 120 GHz for S11 < −15 dB, which corresponds to a fractional bandwidth of 142.85%. The antenna’s performance of bandwidth, impedance match, and radiation gain were enhanced by etching slots on the patches. With the inclusion of the slot, the maximum radiation gain and efficiency of the MPA increased to 15.11 dBi and 85.79% at 80 GHz, which showed an improvement of 2.58 dBi and 12.54%, respectively. The dimension of each patch antenna was 4.3 × 5.3 mm2 . The results showed that the proposed MPA is useful for various existing and emerging communication systems such as ultra-wideband (UWB) communications, RFID systems, massive multiple-output multiple-input (MIMO) for 5G, and radar systems.
  • Spectroscopic characterisation of dissolved organic matter changes in drinking water treatment: From PARAFAC analysis to online monitoring wavelengths

    Shutova, Y.; Baker, A.; Bridgeman, John; Henderson, R.K. (2014-05-01)
    Organic matter (OM) causes many problems in drinking water treatment. It is difficult to monitor OM concentrations and character during treatment processes due to its complexity. Fluorescence spectroscopy is a promising tool for online monitoring. In this study, a unique dataset of fluorescence excitation emission matrixes (EEMs) (n = 867) was collected from all treatment stages of five drinking water treatment plants (WTPs) situated in diverse locations from subtropical to temperate climate. The WTPs incorporated various water sources, treatment processes and OM removal efficiencies (DOC removal 0%–68%). Despite these differences, four common fluorescence PARAFAC components were identified for characterisation of OM concentration and treatability. Moreover, fluorescence component ratios showed site-specific statistically significant correlations with OM removal, which contrasted with correlations between specific UV absorbance at 254 nm (SUVA) and OM removal that were not statistically significant. This indicates that use of fluorescence spectroscopy may be a more robust alternative for predicting DOC removal than UV spectroscopy. Based on the identified fluorescence components, four optical locations were selected in order to move towards single wavelength online OM monitoring.
  • Planning of Hybrid AC-DC Microgrid with High Penetration of Renewable Energy Sources

    Baseer, Muhammad; Mokryani, Geev; Zubo, Rana H.A.; Cox, S. (2019)
    Hybrid AC-DC microgrid (HMG) allows direct integration of both AC distributed generators (DGs) and DC DGs, AC and DC loads into the grid. The AC and DC sources, loads are separate out and are connected to respective subgrid mainly to reduce the power conversion, thus the overall efficiency of the system increases. This paper aims to introduce a novel hybrid AC-DC microgrid planning and design model within a microgrid market environment to maximize net social welfare (NSW). NSW is defined as present value of total demand payment minus present value of total planning cost including investment cost of distributed energy sources (DERs) and converters, operation cost of DERs and the cost of energy exchange with the utility grid subject to network constraints. Scenario Tree approach is used to model the uncertainties related to load demand, wind speed and solar irradiation. The effectiveness of the proposed model is validated through the simulation studies on a 28-bus real hybrid AC-DC microgrid.
  • Planning and Operation of Low Voltage Distribution Networks: A Comprehensive Review

    Al-Jaahfreh, Mohammad A.A.; Mokryani, Geev (2019)
    The low voltage (LV) distribution network is the last stage of the power network, which is connected directly to the end user customers and supplies many dispersed small-scale loads. In order to achieve environmental targets and to address the energy shortage issue, governments worldwide increase the renewable energy sources (RES) into the electricity grid. In addition, different types of low carbon technologies (LCTs) such as electric vehicles (EVs) are becoming widely used. A significant portion of RES and LCTs is penetrated into the LV distribution network, which poses a wide range of challenges. In order to address these challenges, there is a persistent need to develop traditional planning and operation frameworks to cope with these new technologies. In this context, this paper provides a comprehensive review about planning, operation, and management of LV distribution networks. The characteristics, types, and topologies of LV distribution networks plus different aspects of operation and planning are investigated. An insightful investigation of the reasons impacts and mitigation of voltage and current unbalanced in LV networks is provided. Moreover, the main three-phase power flow techniques used to analyze the LV networks are analyzed.
  • Comprehensive review of VPPs planning, operation and scheduling considering the uncertainties related to renewable energy sources

    Ullah, Zahid; Mokryani, Geev; Campean, I. Felician (2019)
    The penetration of renewable energies in the energy market has increased significantly over the last two decades due to environmental concerns and clean energy requirements. The principal advantage of renewable energy resources (RESs) over non-RESs is that it has no direct carbonisation impact on the environment and that it has none of the global warming effects which are caused by carbon emissions. Furthermore, the liberalisation of the energy market has led to the realisation of the virtual power plant (VPP) concept. A VPP is a unified platform for distributed energy resources that integrates the capacities of various renewable energies together for the purpose of improving power generation and management as well as catering for the buying and selling of energy in wholesale energy markets. This review study presents a comprehensive review of existing approaches to planning, operation and scheduling of the VPP system. The methodologies that were adopted, their advantages and disadvantages are assessed in detail in order to benefit new entrants in the power system and provide them with comprehensive knowledge, techniques and understanding of the VPP concept.
  • Resistance spot welding aluminium to magnesium using nanoparticle reinforced eutectic forming interlayers

    Cooke, K.O.; Khan, Tahir I. (2018)
    Successful joining of dissimilar metals such as Al and Mg can provide significant advantages to the automotive industry in the fabrication of vehicle bodies and other important components. This study explores dissimilar joining of Al–Mg using a resistance spot welding process to produce microstructurally sound lap joints and evaluates the impact of interlayer composition on microstructural evolution and the formation of intermetallic compounds within the weld nugget. The results indicated that mechanically sound joints can be produced, with fine equiaxed and columnar dendrites within the weld nugget. The presence of intermetallic compounds was also confirmed by the variation in the microhardness values recorded across the weld zone.
  • Heat treatment effect on wear behaviour of HVOF-sprayed near-nanostructured coatings

    Ben Mahmud, T.; Khan, Tahir I.; Farrokhzad, M.A. (2017)
    This study investigates the effect of heat treatment on changes in microstructure and wear behaviour of WC-NiCr coatings. Two feedstock powders with a similar chemical composition and different particle sizes (near nano-structured WC-17NiCr and microstructured WC-15NiCr) were used. High-velocity oxyfuel spraying technique was used to deposit coatings on to a mild steel substrate using identical spraying parameters. Coated samples were then heat treated in a nitrogen atmosphere at 500 and 700°C. The effect of heat treatment on changes in hardness and wear performance of the coatings was studied using microstructural analysis, micro-hardness indentation and abrasive wear tests. The results showed that the heat treatment increased the hardness of both coatings and a corresponding increase in wear resistance was recorded. The formation of a brittle CrWO4 phase in the microstructured coating resulted in brittle fracture of the coating and this gave lower wear resistance compared to the nanostructured coatings.
  • Investigation of the structural and mechanical properties of micro-/nano-sized Al2O3 and cBN composites prepared by spark plasma sintering

    Irshad, H.M.; Ahmed, B.A.; Ehsan, M.A.; Khan, Tahir I.; Laoui, T.; Yousaf, M.R.; Ibrahim, A.; Hakeem, A.S. (2017-10)
    Alumina-cubic boron nitride (cBN) composites were prepared using the spark plasma sintering (SPS) technique. Alpha-alumina powders with particle sizes of ∼15 µm and ∼150 nm were used as the matrix while cBN particles with and without nickel coating were used as reinforcement agents. The amount of both coated and uncoated cBN reinforcements for each type of matrix was varied between 10 to 30 wt%. The powder materials were sintered at a temperature of 1400 °C under a constant uniaxial pressure of 50 MPa. We studied the effect of the size of the starting alumina powder particles, as well as the effect of the nickel coating, on the phase transformation from cBN to hBN (hexagonal boron nitride) and on the thermo-mechanical properties of the composites. In contrast to micro-sized alumina, utilization of nano-sized alumina as the starting powder was observed to have played a pivotal role in preventing the cBN-to-hBN transformation. The composites prepared using nano-sized alumina reinforced with nickel-coated 30 wt% cBN showed the highest relative density of 99% along with the highest Vickers hardness (Hv2) value of 29 GPa. Because the compositions made with micro-sized alumina underwent the phase transformation from cBN to hBN, their relative densification as well as hardness values were relatively low (20.9–22.8 GPa). However, the nickel coating on the cBN reinforcement particles hindered the cBN-to-hBN transformation in the micro-sized alumina matrix, resulting in improved hardness values of up to 24.64 GPa.
  • Properties of concrete incorporating different nano silica particles

    Alhawat, Musab; Ashour, Ashraf F.; El-Khoja, Amal (2019)
    This paper aims to evaluate the influence of surface area and amount of nano silica (NS) on the performance of concrete with different water/binder (w/b) ratios. For this purpose, 63 different mixes were produced using three NS having three differentsurface areas (52, 250 and 500 m2/g) and w/b ratios (0.4, 0.5 and 0.6). Compressive strengths , workability, water absorption and the microstrcture of concrete mixtures were measured and analysed. and the optimum ratio for each type was determined. The results indicated that the performance of NS particles in concrete is significantly dependent on its amount and surface area as well as w/b ratio. As the w/b ratio increased, a better performance was observed for all types of NS used, whilst NS having 250m2/g surface area was found to be the most effective. The optimum amount of NS ranged from 2 to 5%, depending on NS surface area.
  • SmartWall: Novel RFID-enabled Ambient Human Activity Recognition using Machine Learning for Unobtrusive Health Monitoring

    Oguntala, George A.; Abd-Alhameed, Raed A.; Noras, James M.; Hu, Yim-Fun; Nnabuike, Eya N.; Ali, N.; Elfergani, I.T.; Rodriguez, J. (2019)
    Human activity recognition from sensor readings have proved to be an effective approach in pervasive computing for smart healthcare. Recent approaches to ambient assisted living (AAL) within a home or community setting offers people the prospect of more individually-focused care and improved quality of living. However, most of the available AAL systems are often limited by computational cost. In this paper, a simple, novel non-wearable human activity classification framework using the multivariate Gaussian is proposed. The classification framework augments prior information from the passive RFID tags to obtain more detailed activity profiling. The proposed algorithm based on multivariate Gaussian via maximum likelihood estimation is used to learn the features of the human activity model. Twelve sequential and concurrent experimental evaluations are conducted in a mock apartment environment. The sampled activities are predicted using a new dataset of the same activity and high prediction accuracy is established. The proposed framework suits well for the single and multi-dwelling environment and offers pervasive sensing environment for both patients and carers.
  • New haptic syringe device for virtual angiography training

    Huang, D.; Tang, P.; Wang, X.; Wan, Tao Ruan; Tang, W. (2019-05)
    Angiography is an important minimally invasive diagnostic procedure in endovascular interventions. Effective training for the procedure is expensive, time consuming and resource demanding. Realistic simulation has become a viable solution to addressing such challenges. However, much of previous work has been focused on software issues. In this paper, we present a novel hardware system-an interactive syringe device with haptics as an add-on hardware component to 3D VR angiography training simulator. Connected to a realistic 3D computer simulation environment, the hardware component provides injection haptic feedback effects for medical training. First, we present the design of corresponding novel electronic units consisting of many design modules. Second, we describe a curve fitting method to estimate injection dosage and injection speed of the contrast media based on voltage variation between the potentiometer to increase the realism of the simulated training. A stepper motor control method is developed to imitate the coronary pressure for force feedback of syringe. Experimental results show that the validity and feasibility of the new haptic syringe device for achieving good diffusion effects of contrast media in the simulation system. A user study experiment with medical doctors to assess the efficacy and realism of proposed simulator shows good outcomes.
  • Thin-wall injection molding of polystyrene parts with coated and uncoated cavities

    Masato, Davide; Sorgato, M.; Babenko, Maksims; Whiteside, Benjamin R.; Lucchetta, G. (2018-03-05)
    The paper reports an investigation on the mechanical durability of textured thermoplastic surfaces together with their respective wetting properties. A range of laser-induced topographies with different aspect ratios from micro to nanoscale were fabricated on tool steel inserts using an ultrashort pulsed near infrared laser. Then, through micro-injection moulding the topographies were replicated onto polypropylene surfaces and their durability was studied systematically. In particular, the evolution of topographies on textured thermoplastic surfaces together with their wetting properties were investigated after undergoing a controlled mechanical abrasion, i.e. reciprocating dry and wet cleaning cycles. The obtained empirical data was used both to study the effects of cleaning cycles and also to identify cleaning procedures with a minimal impact on textured thermoplastic surfaces and their respective wetting properties. In addition, the use of 3D areal parameters that are standardised and could be obtained readily with any state-of-the-art surface characterisation system are discussed for monitoring the surfaces' functional response.
  • Mechanical durability of hydrophobic surfaces fabricated by injection moulding of laser-induced textures

    Romano, J.-M.; Gulcur, Mert; Garcia-Giron, A.; Martinez-Solanas, E.; Whiteside, Benjamin R.; Dimov, S.S. (2019-05)
    The paper reports an investigation on the mechanical durability of textured thermoplastic surfaces together with their respective wetting properties. A range of laser-induced topographies with different aspect ratios from micro to nanoscale were fabricated on tool steel inserts using an ultrashort pulsed near infrared laser. Then, through micro-injection moulding the topographies were replicated onto polypropylene surfaces and their durability was studied systematically. In particular, the evolution of topographies on textured thermoplastic surfaces together with their wetting properties were investigated after undergoing a controlled mechanical abrasion, i.e. reciprocating dry and wet cleaning cycles. The obtained empirical data was used both to study the effects of cleaning cycles and also to identify cleaning procedures with a minimal impact on textured thermoplastic surfaces and their respective wetting properties. In addition, the use of 3D areal parameters that are standardised and could be obtained readily with any state-of-the-art surface characterisation system are discussed for monitoring the surfaces’ functional response.
  • Effect of screw configuration on the dispersion and properties of polypropylene/multiwalled carbon nanotube composite

    Ezat, G.S.; Kelly, Adrian L.; Youseffi, Mansour; Coates, Philip D. (2019)
    The effect of extruder screw configuration on the dispersion and properties of compatibilised polypropylene (PP)/multi‐walled carbon nanotube (MCNT) composite is investigated. Three principle screw designs with mainly conveying elements (medium intensity), kneading elements (high intensity), and folding elements (chaotic mixing) were used to prepare polypropylene nanocomposites containing 4wt% of maleic anhydride grafted polypropylene (MAH‐g‐PP) compatibilizer and different nanotube loadings. The effect of each screw configuration and nanotube loading on the tensile, rheological, and electrical properties of the nanocomposites were studied. The screw configurations were found to have a strong influence on the electrical resistivity while only slightly affected the tensile properties of the nanocomposites. Scanning electron microscopy examinations showed that the use of screw configuration consisting of kneading elements promoted the dispersion of nanotubes and resulted in a low electrical percolation at 2wt% of MCNT.
  • Deep face recognition using imperfect facial data

    Elmahmudi, Ali A.M.; Ugail, Hassan (2019-10)
    Today, computer based face recognition is a mature and reliable mechanism which is being practically utilised for many access control scenarios. As such, face recognition or authentication is predominantly performed using ‘perfect’ data of full frontal facial images. Though that may be the case, in reality, there are numerous situations where full frontal faces may not be available — the imperfect face images that often come from CCTV cameras do demonstrate the case in point. Hence, the problem of computer based face recognition using partial facial data as probes is still largely an unexplored area of research. Given that humans and computers perform face recognition and authentication inherently differently, it must be interesting as well as intriguing to understand how a computer favours various parts of the face when presented to the challenges of face recognition. In this work, we explore the question that surrounds the idea of face recognition using partial facial data. We explore it by applying novel experiments to test the performance of machine learning using partial faces and other manipulations on face images such as rotation and zooming, which we use as training and recognition cues. In particular, we study the rate of recognition subject to the various parts of the face such as the eyes, mouth, nose and the cheek. We also study the effect of face recognition subject to facial rotation as well as the effect of recognition subject to zooming out of the facial images. Our experiments are based on using the state of the art convolutional neural network based architecture along with the pre-trained VGG-Face model through which we extract features for machine learning. We then use two classifiers namely the cosine similarity and the linear support vector machines to test the recognition rates. We ran our experiments on two publicly available datasets namely, the controlled Brazilian FEI and the uncontrolled LFW dataset. Our results show that individual parts of the face such as the eyes, nose and the cheeks have low recognition rates though the rate of recognition quickly goes up when individual parts of the face in combined form are presented as probes.
  • Comparison of crystallization characteristics and mechanical properties of polypropylene processed by ultrasound and conventional micro injection molding

    Masato, Davide; Babenko, Maksims; Shriky, Banah; Gough, Timothy D.; Lucchetta, G.; Whiteside, Benjamin R. (2018-10)
    Ultrasound injection molding has emerged as an alternative production route for the manufacturing of micro-scale polymeric components, where it offers significant benefits over the conventional micro-injection molding process. In this work, the effects of ultrasound melting on the mechanical and morphological properties of micro-polypropylene parts were characterized. The ultrasound injection molding process was experimentally compared to the conventional micro-injection molding process using a novel mold, which allows mounting on both machines and visualization of the melt flow for both molding processes. Direct measurements of the flow front speed and temperature distributions were performed using both conventional and thermal high-speed imaging techniques. The manufacturing of micro-tensile specimens allowed the comparison of the mechanical properties of the parts obtained with the different processes. The results indicated that the ultrasound injection molding process could be an efficient alternative to the conventional process.
  • Evaluating Healthcare Governance Using Knowledge-based System to Enhance Quality Management

    Al Khamisi, Yousuf N.; Munive-Hernandez, J. Eduardo; Campean, I. Felician (2018-07)
    Governance perspective plays a vital role in the success of Quality Management in Healthcare Environment (QMHE). In fact QMHE has adopted and applied different quality tools and models in recent times, with some even developing their own quality‐based initiatives. This paper will present an original and novel approach (KB/ES coupled with GAP analysis) to evaluate the effectiveness of governance body in QMHE. The KB system inserts GAP for benchmarking and evaluating the current practices with the desired ones. The KB system will benchmark the current position of governance perspective as part of QMHE with the ideal benchmark one. The results will help healthcare practitioners to improve the governance boy’s gaps and take the correct decisions.
  • Developing a Discrete Event Simulation Methodology to support a Six Sigma Approach

    Hussain, Anees; Munive-Hernandez, J. Eduardo; Campean, I. Felician (2019)
    Competition in the manufacturing industry is growing at an accelerated rate due to globalization trend. This global competition urges manufacturing organizations to review and improve their processes in order to enhance and maintain their competitive advantage. One of those initiatives is the implementation of the Six Sigma methodology to analyze and reduce variation hence improving the processes of manufacturing organizations. This paper presents a Discrete Event Simulation methodology to support a Six Sigma approach for manufacturing organizations. Several approaches to implement Six Sigma focus on improving time management and reducing cycle time. However, these efforts may fail in their effective and practical implementation to achieve the desired results. Following the proposed methodology, a Discrete Event Simulation model was built to assist decision makers in understanding the behavior of the current manufacturing process. This approach helps to systematically define, measure and analyze the current state process to test different scenarios to improve performance. The paper is amongst the first to offer a simulation methodology to support a process improvement approach. It applies an action research strategy to develop and validate the proposed modelling methodology in a British manufacturing organization competing in global markets.
  • Developing a FMEA Methodology to Assess Non-Technical Risks in Power Plants

    Almashaqbeh, Sahar; Munive-Hernandez, J. Eduardo; Khan, M. Khurshid (2018-07)
    Risk Management is one of the most relevant approaches and systematic application of strategies, procedures and practices management that have been introduced in literature to identifying and analysing risks which exist through the whole life of a product or a process. As a quality management tool, the novelty of this paper suggests a modified Failure Modes and Effect Analysis (FMEA) for understanding the non-technical risk comprehensively, and to attain a systemic methodology by decomposing the risk for nine risk categories including an appropriate 84 Risk Indicators (RI's) within all those categories through the Life Cycle (LC) stages of power plants. These risk categories have been identified as: economic risks, environmental and safety health risks, social risks, technological risks, customer/demand risks, supply chain risks, internal and operational business process risks, human resources risks and management risks. These indicators are collected from literatures. The enhanced FMEA has combined the exponential and the weighted geometric mean (WGM) to calculate the Exponential Weighted Geometric Mean-RPN (EWGM-RPN). The EWGM-RPN can be used to evaluate the risk level, after which the high-risk areas can be determined. Subsequently, effective actions either preventive or corrective can be taken in time to reduce the risk to an acceptable level. However, in this paper the FMEA will not adapt an action plan. Due to that, all RPN's will be considered depending on the point scale (1 to 5) afterward, the results will be combined and extended later with AHP. This developed methodology is able to boost effective decision- making about risks, improve the awareness towards the risk management at power plants, and assist the top management to have an acceptable and preferable understanding of the organisation than lower level managers do who are close to the day-to-day (tactical plan). Additionally, this will support the organisation to develop strategic plans which are for long term. And the essential part of applying this methodology is the economic benefit. Also, this paper includes developed sustainability perspective indicators with a new fourth pillar, which is the technological dimension. The results of the analysis show that the potential strategic makers should pay special attention to the environmental and internal and operational business process risks. The developed methodology will be applied and validated for different power plants in the Middle East. An expanded validation is required to completely prove drawbacks and benefits after completing the Analytical Hierarchy Process (AHP) model.

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