Now showing items 1-20 of 10191

    • Machine Learning for 3D Visualisation Using Generative Models

      Ugail, Hassan; Mehmoud, Irfan; Taif, Khasrouf M.M.; Yarmouk University (University of BradfordFaculty of Engineering and Informatics. School of Media, Design and Technology, 2020)
      One of the state-of-the-art highlights of deep learning in the past ten years is the introduction of generative adversarial networks (GANs), which had achieved great success in their ability to generate images comparable to real photos with minimum human intervention. These networks can generalise to a multitude of desired outputs, especially in image-to-image problems and image syntheses. This thesis proposes a computer graphics pipeline for 3D rendering by utilising generative adversarial networks (GANs). This thesis is motivated by regression models and convolutional neural networks (ConvNets) such as U-Net architectures, which can be directed to generate realistic global illumination effects, by using a semi-supervised GANs model (Pix2pix) that is comprised of PatchGAN and conditional GAN which is then accompanied by a U-Net structure. Pix2pix had been chosen for this thesis for its ability for training as well as the quality of the output images. It is also different from other forms of GANs by utilising colour labels, which enables further control and consistency of the geometries that comprises the output image. The series of experiments were carried out with laboratory created image sets, to pursue the possibility of which deep learning and generative adversarial networks can lend a hand to enhance the pipeline and speed up the 3D rendering process. First, ConvNet is applied in combination with Support Vector Machine (SVM) in order to pair 3D objects with their corresponding shadows, which can be applied in Augmenter Reality (AR) scenarios. Second, a GANs approach is presented to generate shadows for non-shadowed 3D models, which can also be beneficial in AR scenarios. Third, the possibility of generating high quality renders of image sequences from low polygon density 3D models using GANs. Finally, the possibility to enhance visual coherence of the output image sequences of GAN by utilising multi-colour labels. The results of the adopted GANs model were able to generate realistic outputs comparable to the lab generated 3D rendered ground-truth and control group output images with plausible scores on PSNR and SSIM similarity index metrices.
    • Public Expenditure and Poverty Reduction: Evidence from Nigeria

      Jalilian, Hossein; Batonyi, Gabor; Obiechina, Michael E. (University of BradfordFaculty of Management, Law and Social Sciences, 2020)
      Theoretical and empirical literature suggest that public expenditure plays very important role in economic growth, especially in the developing countries. Available statistics show that Nigeria’s 5-year average annual real public expenditure/GDP ratio grew during the greater part of the study period 1981-2015, while the 5-year average annual real GDP growth and real GDP per capita growth rates are positive during the same study period, except for 1981-1985 and 1986-1990, respectively. The incidence of poverty, however, maintained upward movement, except for 2006-2010. The foregoing interactions have been seldom, the focus of empirical studies in Nigeria. This study examines the effects of public expenditure on economic growth and poverty reduction in Nigeria from 1981-2015, using variants of two models and simulation exercise: augmented Solow growth model and growth-poverty model. Real public expenditure/GDP ratio is used as the policy variable and the simulation duration is for 5-years, 2016-2020. We use the autoregressive distributed lag (ARDL) bounds testing procedure by Pesaran et al. (2001) to estimate the two models, given that the annual data used for the models’ estimations were integrated of order I(1) and I(0) and small sample size. The results from the two models confirmed that public expenditure increases economic growth, though not significant, while economic growth does not reduce poverty. The same findings are confirmed through the simulation exercise. We, however, offer measures that would ensure growth and poverty reduction in Nigeria; public expenditure switch that encourages more investments in capital public expenditure, social sector public expenditure and private capital investment.
    • Functional Analysis of Polished-edge Discoidal Knives of the British Isles

      Not named; Metzger, Melissa A. (University of BradfordSchool of Archaeology and Forensic Science. Faculty of Life Science, 2018)
      Polished-edge discoidal knives are part of the lithic material culture from the British Isles with an approximate Late Neolithic date. These artefacts are manufactured in three basic shapes: circular to D-shaped, triangular, and broad leaf to lozenge (Clark 1929). The aim of this project was to explore the function of polished-edge discoidal knives. To achieve this aim, the following objectives were completed: Objective 1: Develop a broad understanding of the literature surrounding polished-edge discoidal knives; Objective 2: Develop a database containing all the available information regarding the known knives for study in this project and as a tool to help further research and select archaeological samples for study based on type, condition, find location, and current location; Objective 3: Understand how these tools were used; and Objective 4: Review all data and produce a narrative about polished-edge discoidal knives’ function in Late British Neolithic Society. This project has revealed that these knives were possibility used for activities involving birch bark, clay, or other wood types. This research has also produced a database of knives, a modern distribution map, a revised typology, an archaeological date and possible contexts, and an object itinerary.
    • Evaluating the use of a theory-based intervention to improve medication-taking behaviours: A Longitudinal mixed-methods study in patients with Pulmonary Arterial Hypertension. Applying Health Belief Model theory to understand patients’ medication and disease beliefs and using this to develop and evaluate targeted interventions delivered by a pharmacist to improve medication adherence

      Morgan, Julie D.; Quinn, Gemma L.; Palmer, Timothy M.; Jackson, Michael P. (University of BradfordFaculty of Life Sciences School of Pharmacy and Medical Sciences, 2020)
      Pulmonary Arterial Hypertension (PAH) is a rare incurable condition affecting both the cardiac and respiratory systems. Patients living with PAH face the burden of both intensive medication regimens and debilitating disease symptoms. This study’s primary aim was to identify patients’ medication-taking behaviours and beliefs using a framework derived from the extended health belief model (EHBM), and to use this information to deliver personalised interventions to improve medication-taking behaviours. A mixed-methodology longitudinal study design recorded patients’ parameters over a 12-month period. Thirteen participants from Northern Ireland completed the study. The results showed that the level of high-adherence to PAH medicines, as assessed using the MARS questionnaire was 80%, but this value differed when assessed via pill counting and interview data. There was a trend to improvement in observed and predicted medication adherence over the study duration. Participants’ beliefs showed a non-statistical increase in the specific-necessity beliefs and a reduction in general-overuse belief. This study added to the EHBM new constructs of trust and support in being able to better predict nonadherent behaviours. Key medication-taking themes were self-confidence, perceived ranking of medicines, uncertainty and knowledge. This study developed important learning that can be applied to future research on behavioural health studies.
    • Development of Three-Dimensional Learning Materials for Key Stage 3 Design and Engineering Students. An Introductory Aid to SolidWorks CAD Teaching for Secondary Schools

      Not named; Hill, Elliot (University of BradfordFaculty of Engineering and Informatics, 2018)
      This thesis looks at the development of a physical 3D learning model designed to introduce key stage 3 students to the basics of SolidWorks with the ultimate aim of developing the model to a level where schools can use it in the education of students. The purpose of this thesis is to identify any problems with the author’s final year undergraduate project (a three-dimensional card model of Tower Bridge, which features instructions to help teach the fundamentals of SolidWorks), and to create a new learning material based on those findings. The creation of the new learning material was in part based on feedback during visits to local secondary schools. Small scale user trials were also conducted throughout the product development in order to gain first-hand insight into how the solution was meeting its objectives, i.e. being a viable learning pack for Secondary Schools. The overall project aim was to create 3 – Dimensional teaching material designed to assist in classrooms for secondary education. This aim was partially realised in that a clear and concise learning path was created. However, due to lack of engagement from local secondary schools it was not feasible to conduct user trials. These trials and subsequent review have been suggested as possible future work. It should be noted that apart from the Tower Bridge product, reviewed in chapter 3, all work presented within this thesis was conducted as part of this master study.
    • Robust Noise Filtering techniques for improving the Quality of SODISM images using Imaging and Machine Learning

      Not named; Algamudi, Abdulrazag A.M. (University of BradfordSchool of Electrical Engineering and computer Science. Faculty of Engineering and Informatics, 2020)
      Life on Earth is strongly related to the Sun, which makes it a vital star to study and understand. To improve our knowledge of the way the Sun works, many satellites have been launched into space to monitor the Sun‟s activities where the one of main focus is the effect of these activities on the Earth‟s climate; PICARD is one such satellite. Due to the noise associated with SODISM images, the clarity of these images and the appearance of solar features are affected. Image denoising and enhancement are the main techniques to improve the visual appearance of SODISM images. Affective de-noising algorithm methods depend on a proper detecting of noise present in the image. The aim is to identify which type of noise is present in the image. To reach this point, supervised machine-learning (ML) classifier is used to classify the type of noise present in the image. Furthermore, this work introduces a novel technique developed to enhance the quality of SODISM images. In this thesis, the Modified Undecimated Discrete Wavelet Transform (M-UDWT) technique is used to de-noise and enhance the quality of SODISM images. The proposed method is robust and effectively improves the quality of SODISM images, and produces more precise information and clear feature are brought out. In addition, the non wavelet enhancement is developed as well in this thesis. The results of this algorithm is discussed. The new methods are also assessed using two different methods: subjective (by human observation) and objective (by calculation)
    • Gender inequality in education: An Investigation into the effects of School Management Practices on Health Behaviours of Female Students. (A Study of Selected Senior Secondary Schools in Lagos State)

      Archibong, Uduak E.; Walton, Sean; Eyanuku, Julius P. (University of BradfordSchool of Health Studies. Diversity and Inclusion Management, 2020)
      This research explores gender inequality in education, with a focus to examine the implications of gender disparities in schools on girls’ health and education. The study sought to investigate whether school management practices is a possible factor impacting the health behaviours of female students in senior secondary schools in Lagos, Nigeria. The study employed mixed methods design and gathered primary data in two consecutive phases, in line with sequential explanatory design. Data in Phase one was gathered through the use of questionnaire while phase 2 gathered primary data using semi-structured interviews to complement survey data. The sample frame included 2 public secondary schools, 42 students, 9 teachers, 1 vice principal and 2 principals. Quantitative data were analyzed using Statistical Package for Social Sciences (SPSS), while qualitative data were analyzed with help of ATLAS.ti. The findings of the study revealed school related barriers that influence high absenteeism and dropout among girls. Further findings also show the schools lack appropriate school management policies that promote healthful behaviours and encourage positive learning environment for girls. The researcher recommends leadership and school management training for school principals and their deputies, improving quality of health instruction in the curriculum, developing strict policy against school-related gender-based violence and adopting health-promoting policies.
    • From Bradford Moor to Silver Dale. The life, work, and legacy of W. Riley, 1866-1961

      Sheeran, George; Copeland, David M. (University of BradfordSchool of Lifelong Education and Development, 2008)
      This thesis presents the first full account of the life and achievements of Bradford-born W. Riley (1866-1961), once internationally known as a popular and prolific Yorkshire author. Before becoming a famous writer, he was Managing Director of the successful Bradford Optical Lantern Company, Riley Brothers and was also, for 75 years, a Methodist local preacher and an important layman within northern Methodism. He wrote 39 books, published many stories and articles, and was a busy lecturer. Riley located most of his 30 novels in the Yorkshire Dales and has left a legacy of vivid portraits of people and places in the dales that he knew and loved. This biography of Riley draws upon material never seen hitherto, expanding upon the author's diffident autobiography. The complete bibliography of his extensive writings includes much new and long-lost material. In presenting Riley to a new generation, this account places him in context with his contemporaries. Riley proclaimed his Christianity sympathetically and attractively to his receptive public in much of his output. This thesis includes an insight into the spiritual life, outlook and thinking of a popular and much-respected committed and active Methodist local preacher. Riley's life story is the account of a remarkably successful, self-motivated Victorian. He was a household name in his time, both in Yorkshire and internationally. The research for this thesis has uncovered important material relating to Riley, which will be held in the W. Riley Archive, at the Special Collections Section of the University of Bradford J.P. Priestley Library.
    • Addressing Food Waste and Loss in Nigerian Food Supply Chain: Use of Lean Six Sigma and Double-Loop Learning

      Hussain, Zahid I.; Mishra, J.; Kolawole, Olushola A. (University of BradfordFaculty of Management and Law, 2020)
      The purpose of this research is to explore how Double Loop Learning (DLL) and Lean Six Sigma tool (i.e. DMAIC-Defined, Measure, Analysis, Improvement, and Control) can be used to reduce Food Waste and Loss (FWL) in the processing and distribution units of the Food Supply Chain (FSC) in the developing countries. This study is motivated base on the identified research problem of which about one-third of every food produce is wasted yearly, which equates to 1.3 billion tonnes of food throughout the entire food supply chain, with up to 50% of FWL occur at the pre-consumption stage of FSC in the developing countries. The economic values of FWL in Sub-Saharan Africa amount to $230 billion yearly. Therefore, the focus has been on how to reduce the magnitude of FWL at the pre-consumption stage of the FSC in the developing countries while promoting continuous improvement practices. Though technological, environmental, and Supply Chain Strategies (SCS) aimed at reducing FWL are effective in some parts of the world but the effectiveness of those strategies in some countries is hindered by poor supply chain activities. This research adopted a qualitative research method through the use of multiple case study strategies, with the aid of semi-structured interviews, observation, and documents to explore the perception, understanding, and experience of the FSC stakeholders on how DMAIC-DLL can be used to reduce FWL. The findings of this study show that with the DMAIC-DLL framework, the root causes of FWL at the pre-consumption stage were identified. The study found that some Lean tools, employee improvisation, learning practices are some of the strategies that could be used in reducing FWL. The findings suggest that experiential learning, collaborative learning, and on-job training are effective learning mechanisms that could be used to promote learning in the adoption of DMAIC-DLL in the FSC. Therefore, this research contributes towards the ongoing debate on how to reduce FWL as well as the wider debate learning mechanisms that support continuous improvement practices. Future research should explore how DMAIC-DLL can be extended to other settings other than the food industry.
    • The role of inter-organisational knowledge management in the UEA's public policing sector

      Not named; Alghafli, Saif (University of BradfordFaculty of Management, Law & Social Sciences, 2020)
      Inter-organisational knowledge sharing between airport security organisations has become increasingly vital to maintain the highest standards of security and public safety. Social networks are considered a significant space for knowledge sharing within and across organisations. The purpose of this research is to investigate inter-organisational knowledge sharing in social media between key organisations in policing and airport security. A cross-sectional case study strategy combining qualitative and quantitative methods was employed to investigate the use of social media in inter-organisational knowledge sharing in the context of airport security in the UAE. Findings showed that the structural characteristics within knowledge sharing were highly centralised and polarised with low intensity in knowledge sharing. Social capital was constrained at a relational level due to cultural factors of trust, risk aversion and power distance that influenced a closed culture and reduced the scope for tacit knowledge sharing practices as well as low level cognitive capital. Analysis of dimensions of the SECI model for knowledge creation revealed that knowledge and the process of knowing was impacted by cultural distinctions that constrained socialisation, externalisation, combination and internalisation processes. The key barriers to knowledge sharing were identified and associated with trust, risk aversion, organisational culture, resource constraints and interoperability factors. This study makes a contribution to theory and practice in terms of the relationship between social capital dimensions and knowledge creation processes and the characteristics of knowledge-sharing within social media. The study further adds to knowledge on the antecedents of inter-organisational knowledge sharing, particularly in the Arabic context.
    • Creating Copreneurial Identities. A phenomenological study of how copreneurs make sense of their lived experience of work and family life in copreneurial business

      Cunliffe, Ann L.; Smith, Andrew J.; Parkinson, Caroline; Muscatelli, Sophie M. (University of BradfordFaculty of Management, Law and Social Science, School of Management, 2020)
      The purpose of my research is to examine how copreneurial couples make sense of their lived experience of working in a copreneurial business and shape their mutual identity. The research context is copreneurs operating micro-businesses in the Greek leisure and tourism industry. Given the size of the tourism industry worldwide and the fact that many businesses within this sector are family-owned, this is an important area of inquiry. The aim is twofold: 1. To build theory in the field of entrepreneurship by focusing specifically on the undertheorized topic of how copreneurs understand and shape their identity and responsibilities within copreneurial businesses 2. To bring an under-utilized methodology to entrepreneurship studies, that of interpretive phenomenological analysis (IPA), as a means of enhancing the understanding of the lived experience of copreneurs. Drawing on phenomenological philosophy, IPA foregrounds the meanings research participants give to their experience and therefore offers rich interpretations from copreneurial couples While taking an idiographic approach, which focuses on the first-person experience of copreneurs in a particular context, the findings will resonate with other copreneurs. The contribution of this research therefore lies in advancing our understanding of copreneurship and familial entrepreneurship by elucidating the interrelationship between personal and business partnerships. The study makes visible the often invisible recursive links between paid work and family life for men and women
    • Fast and Accurate Image Feature Detection for On-The-Go Field Monitoring Through Precision Agriculture. Computer Predictive Modelling for Farm Image Detection and Classification with Convolution Neural Network (CNN)

      Abd-Alhameed, Raed A.; Sheriff, Ray E.; Mahieddine, Fatima; Abdullahi, Halimatu S. (University of BradfordFaculty of Engineering and Informatics, School of Electrical Engineering and Computer Science, 2020)
      This study aimed to develop a novel end-to-end plant diagnosis model for the analysis of plant health conditions in near real-time to optimize the rate of production on farmlands for an intensive, yet environmentally safe farming production to preserve the natural environment. First, field research was conducted to determine the extent of the problems faced by farmers in agricultural production. This allowed us to refine the research statement and the level of technology involved in the production processes. The advantages of unmanned aerial systems were exploited in the continuous monitoring of farm plantations to develop automated and accurate measures of farm conditions. To this end, this thesis applies the Precision Agricultural technology as a data based management system that takes into account spatial variations by using the Global Positioning System, Geographical Information System, remote sensing, yield monitors, mapping, and guidance system for variable rate applications. An unmanned aerial vehicle embedded with an optic and radiometric sensor was used to obtain high spectral resolution images of plantation status during normal production/growth cycle. Then, an ensemble of classifiers with Convolution Neural Networks (CNN) was used as off the shelf feature extractor to train images to develop an end-to-end feature detection and multiclass classification system for plant overall health’s conditions. Whereby previous works have concentrated on using CNN as off the shelf feature extractor and model training to detect only plant diseases from plants. To date, no research has yet been carried out to develop an end-to-end model for the overall plant diagnosis system. Previous studies focused on the detection of diseases at any given time, making it difficult to implement comprehensive real-time PA systems. Applying the pretrained model to the new images showed that the model can accurately predict any plant condition with an average of 97% accuracy.
    • Investigation of Nigerian Ethno-medicinal Plants as Potential Sources of Cytotoxic and Anti-plasmodial Compounds. Biological activity of Vitellaria paradoxa, Cyperus articulatus, Securidaca longepedunculata and semi-synthetic halogenated analogues of cryptolepine isolated from Cryptolepis sanguinolenta

      Falconer, Robert A.; Shnyder, Steven D.; Wright, Colin W.; Abacha, Yabalu Z. (University of BradfordSchool of Pharmacy and Medical Sciences, Faculty of Life Sciences, 2020)
      Natural products are acknowledged sources of novel compounds for use in the treatment of diseases such as cancer, malaria, and human African trypanosomiasis. However, health burdens of such diseases still remain high, with drug resistance leading to failure of current medication. Therefore, there is a need for new treatments, and this project considers the potential of Nigerian ethno-medicinal plants and their products. Firstly, the aims were to isolate cytotoxic compounds through bio-guided evaluation and fractionation from 3 medicinal plants; Vitellaria paradoxa, Cyperus articulatus and Securidaca longepedunculata used traditionally in the treatment of cancer in North-East Nigeria. Extracts from S. longepedunculata were the most active when assessed in a panel of cancer cell lines, with IC50 values below 10 µg/ml, whilst fractions isolated from V. paradoxa and C. articulatus were moderately cytotoxic and able to overcome drug resistance mechanisms in drug resistant cell lines. In the second part of the thesis, novel cryptolepine analogues were semi-synthesized using environmentally friendly methods and evaluated for cytotoxic, anti-plasmodial and anti-trypanosomal activity. The compounds were found to be highly cytotoxic in cancer cell lines with the ability to overcome drug resistant mechanisms, with sub-µM IC50 values, and were also active against drug resistant strains of Plasmodium parasites in addition to Trypanosoma brucei, with IC50 values below 500 nM, and 300 pM respectively.
    • Developing city-level sustainability indicators in the MENA region with the cases of Benghazi and Amman

      Anand, Prathivadi B.; El- Hegazi, Serag (University of BradfordSchool of Management, Faculty of Management and Law, 2021)
      The development of a methodological framework for local and institutional sustainability assessment can be helpful for planners and urban governments. The aim of this research is to develop an approach to local and institutional sustainability assessment (ALISA). It is designed to assist in the clarification, formulation, preparation, selection, and ranking of key indicators to facilitate the assessment of city sustainability at the local and institutional level in the Middle Eastern and North African (MENA) cities. The ALISA methodological framework is developed using joint documentary and analysed data in the two case studies of Benghazi and Amman. The data for this also includes focus-group discussions, semi-structured interviews, and questionnaires that reflect the approach required in order to develop a combined framework that assists the development of sustainability indicators. The initial list of proposed sustainability indicators for Benghazi contains 37 indicators. This list was developed based on logical information and procedure which has been supported by consultants and specialists in sustainability and urbanization from the University of Benghazi in the form of workshops as well as searching through the literature on sustainable development. Similarly, with support from consultants and specialists in sustainability and urbanization from the Applied science University a list of 36 indicators was also developed in Amman. Both lists were given to the local communities in Benghazi and Amman to be ranked based on priority to identify two final lists of sustainability indicators. The results indicated that economic and social indicators were highly ranked in Benghazi and Amman, respectively.
    • The Impact of the Pandemic on Mental Health in Ethnically Diverse Mothers: Findings from the Born in Bradford, Tower Hamlets and Newham COVID-19 Research Programmes

      McIvor, C.; Vafai, Y.; Kelly, B.; O'Toole, S.E.; Hays, M.; Badrick, E.; Iqbal, Halima; Pickett, K.E.; Cameron, C.; Dickerson, J. (2022-11)
      Restrictions implemented by the UK Government during the COVID-19 pandemic have served to worsen mental health outcomes, particularly amongst younger adults, women, those living with chronic health conditions, and parents of young children. Studies looking at the impact for ethnic minorities have reported inconsistent findings. This paper describes the mental health experiences of mothers from a large and highly ethnically diverse population during the pandemic, using secondary analysis of existing data from three COVID-19 research studies completed in Bradford and London (Tower Hamlets and Newham). A total of 2807 mothers participated in this study with 44% White British, 23% Asian/Asian British Pakistani, 8% Other White and 7% Asian/Asian British Bangladeshi backgrounds. We found that 28% of mothers experienced clinically important depressive symptoms and 21% anxiety symptoms during the pandemic. In unadjusted analyses, mothers from White Other, and Asian/Asian British Bangladeshi backgrounds had higher odds of experiencing symptoms, whilst mothers from Asian/Asian British Indian backgrounds were the least likely to experience symptoms. Once loneliness, social support and financial insecurity were controlled for, there were no statistically significant differences in depression and anxiety by ethnicity. Mental health problems experienced during the pandemic may have longer term consequences for public health. Policy and decision makers must have an understanding of the high risk of financial insecurity, loneliness and a lack of social support on mother’s mental health, and also recognise that some ethnic groups are far more likely to experience these issues and are, therefore, more vulnerable to poor mental health as a consequence.
    • Democracy under God: Constitutions, Islam and Human Rights in the Muslim World

      Ahmed, D.; Abbasi, Muhammad Z. (Cambridge University Press, 2023-02)
      The place of Islam in constitutions invites fierce debate from scholars and politicians alike. Many of these debates assume an inherent conflict between constitutional Islam and 'secular' values of liberal democracy and human rights. Using case studies from several Muslim-majority states, this book surveys the history and role of Islam in constitutions. Tracing the origins of constitutional Islam, Dawood Ahmed and Muhammad Zubair Abbasi argue that colonial history and political bargaining were pivotal factors in determining whether a country adopted Islam, and not secularism, in its constitution. Contrary to the common contention that the constitutional incorporation of Islam is generally antithetical to human rights, Ahmed and Abbasi show not only that Islam has been popularly demanded and introduced into constitutions during periods of 'democratization' and 'modernization' but also that constitutional Islamization has frequently been accompanied by an expansion in constitutional human rights.
    • Fabrication, Characterisation and Optimisation of Biodegradable Scaffolds for Vascular Tissue Engineering Application of PCL and PLGA Electrospun Polymers for Vascular Tissue Engineering

      Sefat, Farshid; Youseffi, Mansour; Bazgir, Morteza (University of BradfordFaculty of Engineering & Informatics, Department of Biomedical and Electronics Engineering, 2021)
      Annually, about 80,000 people die in the United Kingdom due to myocardial infarction, congestive heart failure, stroke, or from other diseases related to blood vessels. The current gold standard treatment for replacing the damaged blood vessel is by autograft procedure, during which the internal mammary artery (IMA) graft or saphenous vein graft (SVG) are usually employed. However, some limitations are associated with this type of treatment, such as lack of donor site and post-surgery problems that could negatively affect the patient’s health. Therefore, this present work aims to fabricate a synthetic blood vessel that mimics the natural arteries and to be used as an alternative method for blood vessel replacement. Polymeric materials intended to be used for this purpose must possess several characteristics including: (1) Polymers must be biocompatible; (2) Biodegradable with adequate degradation rate; (3) Must maintain its structural integrity throughout intended use; (4) Must have ideal mechanical properties; and (5) Must encourage and enhance the proliferation of the cells. The feasibility of using synthetic biodegradable polymers such as poly (ε- caprolactone) (PCL) and poly (lactide-co-glycolic acid) (PLGA) for fabricating tubular vascular grafts was extensively investigated in this work. Many fundamental experiments were performed to develop porous tissue- engineered polymeric membranes for vascular graft purposes through electrospinning technique to achieve the main aim. Electrospinning was selected since the scaffolds produced by this method usually resemble structural morphology similar to the extracellular matrix (ECM). Hence, four 6mm in diameter tubular shape vascular grafts PCL only, PLGA only, coaxial (core-PCL and shell-PLGA), and bilayer (inner layer-PCL and outer layer-PLGA) was designed and fabricated successfully. The structure and properties of each scaffold membrane were observed by scanning electron microscopy (SEM), and these scaffolds were fully characterized by Fourier-transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), thermogravimetric analysis (TGA), water contact angle measurements, mechanical tensile test, as well as cell culture studies were carried out by seeding human umbilical vein cells (HUVEC) and human vascular Fibroblast cells (HVF). Moreover, all polymeric grafts underwent degradation process, and the change in their morphological structure properties was studied over 12 weeks at room temperature. All scaffolds were also exposed to a controlled temperature of 37°C for four weeks, in phosphate-buffered saline solution (pH, 7.3). It was found that all scaffolds displayed exceptional fibre structure and excellent degradability with adequate steady weight-loss confirming the suitability of the fabricated scaffolds for tissue engineering applications. The coaxial and bilayer scaffolds degraded at a much slower (and steadier) rate than the singular PCL and PLGA tubular scaffolds. Coaxial grafts fabricated via coaxial needle showed an increase in their fibre diameter and pore size volume than other membranes, but also showed to have significant tensile strength, elongation at fracture, and Young’s modulus. To conclude, all scaffolds have demonstrated to be reliable to adhere and proliferate HUVEC, and HVF cells, but these cells were attracted to the PLGA membrane more than other fabricated membranes.
    • Automated Prediction of Solar Flares Using SDO Data. The Development of An Automated Computer System for Predicting Solar Flares Based on SDO Satellite Data Using HMI Images Analysis, Visualisation, and Deep Learning Technologies

      Qahwaji, Rami S.R.; Abd-Alhameed, Raed A.; Abed, Ali K. (University of BradfordSchool of Computing, Informatics & Media, 2021)
      Nowadays, space weather has become an international issue to the world's countries because of its catastrophic effect on space-borne and ground-based systems, and industries, impacting our lives. One of the main solar activities that is considered as a major driver of space weather is solar flares. Solar flares can be defined as an enormous eruption in the sun's atmosphere. This phenomenon happens when magnetic energy stored in twisted magnetic fields, usually near sunspots, is suddenly released. Yet, their occurrence is not fully understood. These flares can affect the Earth by the release of massive quantities of charged particles and electromagnetic radiation. Investigating the associations between solar flares and sunspot groups is helpful in comprehending the possible cause and effect relationships among solar flares and sunspot features. 01 This thesis proposes a new approach developed by integrating advances in image processing, machine learning, and deep learning with advances in solar physics to extract valuable knowledge from historical solar data related to sunspot regions and flares. This dissertation aims to achieve the following: 1) We developed a new prediction algorithm based on the Automated Solar Activity Prediction system (ASAP) system. The proposed algorithm updates the ASAP system by extending the training process and optimizing the learning rules to the optimize performance better. Two neural networks are used in the proposed approach. The first neural network is used to predict whether a specific sunspot class at a particular time is likely to produce a significant flare or not. The second neural network is used to predict the type of this flare, X or M-class. 2) We proposed a new system called the ASAP_Deep system built on top of the ASAP system introduced in [6] but improves the system with an updated deep learning-based prediction capability. In addition, we successfully apply Convolutional Neural Network (CNN) to the sunspot group image without any pr-eprocessing or feature extraction. Moreover, our system results are considerably better, especially for the false alarm ratio (FAR); this reduces the losses resulting from the protection measures applied by companies. In addition, the proposed system achieves a relatively high score of True Skill Statistic (TSS) and Heidke Skill Score (HSS). 3) We presented a novel system that used the Deep Belief Networks (DBNs) to predict the solar flares occurrence. The input data are SDO/HMI Intensitygram and Magnetogram images. The model outputs are "Flare or No-Flare" of significant flare occurrence (M and X-class flares). In addition, we created a dataset from the sunspots groups extracted from SDO HMI Intensitygram images. We compared the results obtained from the complete suggested system with those of three previous flare forecast models using several statistical metrics. In our view, these developed methods and results represent an excellent initial step toward enhancing the accuracy of flare forecasting, enhance our understanding of flare occurrence, and develop efficient flare prediction systems. The systems, implementation, results, and future work are explained in this dissertation.
    • Ethnic minority inclusion: a means to achieving greater employee performance. (A study of selected transnational companies in Nigeria)

      Archibong, Uduak E.; Walton, Sean; Utam, Kingsley U. (University of BradfordFaculty of Health Sciences, Centre for Inclusion and Diversity, 2020)
      Advances in transportation and communication have resulted in the ease of migration of people across transnational borders and the internationalisation of business organisations. These events have brought about changing workforce demographics, intense global competition, and the quest for talents across the world. These trends have made workforce diversity inevitable for transnational companies (TNCs). TNCs operating in Nigeria face a peculiar problem as there are two layers of ethnic diversity created by the country’s enormous diversity. The task of managing the layers of diversity is complicated by the weak legal and institutional provisions for the management of diversity in public and private firms. Also, there is a general lack of awareness about diversity and inclusion (D&I) in Nigeria; hence, the field has received scant attention from academics and practitioners. This study explored the D&I policies and strategies adopted by selected subsidiaries of TNCs in Nigeria and describes ethnic minority employee perception of D&I policies and the effects these policies have on performance at the individual and team levels. To achieve these objectives, it aims to provide answers to two research questions: “What are the organisational policies and strategies that enhance diversity and the inclusion of ethnic minority employees in TNCs; and how do D&I policies and strategies impact the performance of individuals and groups within the organisation?” The study adopted the exploratory mixed-methods design to collect qualitative and quantitative data for analysis. The qualitative data included the primary and secondary sources; and involved semi-structured interviews with six senior managers in four subsidiaries of TNCs and documentary analysis. While the quantitative data involved a survey of 133 employees across the four participating companies. The reflexive thematic analysis method was used to analyse the qualitative data, leading to the generation of themes; while the quantitative data were analysed using the descriptive statistical technique. Findings reveal the presence of varying degrees of D&I initiatives among the participating organisations, ranging from well-articulated and established programmes in one company to medium range policies in two companies, and no initiatives in one company. Findings also suggest a high level of inclusion of ethnic minority employees at the group or team level and a low inclusion at the top management level. Also, participants generally report a positive perception of the relationship between workforce D&I and performance at both the individual and team level. Some of the variables used to indicate inclusion are access to information, participation in group activities, membership of informal networks, participation in decision-making and participation in meeting with supervisor and senior management. Similarly, some of the performance variables include creativity, innovation, timely completion of tasks and quality of work output. Finally, the findings from the study contributed to filling the gap in the literature as well as empirically highlighting the D&I policies operational in TNCs in Nigeria. The study recommends that diversity policy-makers pay attention to the additional layer of diversity while developing global policies for a more inclusive organisational environment. This study has provided valuable insights into the policies and practices as well as employee perception of diversity in light of the dearth of studies from the Nigerian context. Despite some inherent limitations, it serves as a starting point that could ignite the interest of other researchers and practitioners in the fields of diversity.
    • How privacy practices affect customer commitment in the sharing economy: A study of Airbnb through an institutional perspective

      Chen, S.; Tamilmani, Kuttimani; Tran, K.T.; Waseem, Donia; Weerakkody, Visanth J.P. (Elsevier Inc., 2022-11)
      Privacy is an emerging issue for home-sharing platforms such as Airbnb. Home-sharing providers (business customers) are subject to both digital privacy risks (e.g., data breaches and unauthorized data access) and physical privacy risks (e.g., property damage and invasion of their personal space). Therefore, platforms need to strengthen their institutions of privacy management to protect the interests of providers and maintain their commitment. By applying the micro-level psychological aspect of institutional theory, our research investigates how providers decide their level of commitment to a platform by evaluating the institutions of the platform’s privacy management. Our survey recruited 380 Airbnb providers from the Prolific panel. Structural equation modeling analysis shows that both physical and digital privacy practices strengthen providers’ legitimacy judgment of the platform’s privacy management and subsequently increase their commitment to the platform. Our theoretical contribution lies in revealing the effects of physical and digital privacy practices on B2B relationships from an institutional perspective. Our research is among the first to provide an integrative framework illustrating providers’ psychological process of legitimacy judgement. It also has practical implications for sharing economy platforms to manage privacy.