Now showing items 61-80 of 1443

    • 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.
    • 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.
    • Modelling and Simulation of Carbon Dioxide Transportation in Pipelines: Effects of Impurities

      Rahmanian, Nejat; Mujtaba, Iqbal M.; Peletiri, Suoton P. (University of BradfordFaculty of Engineering and Informatics, 2020)
      Carbon dioxide capture, transportation, and storage has been identified as the most promising way to reduce anthropogenic carbon dioxide (CO2) released into the atmosphere. Efforts made to achieve this purpose include the Paris (Climate) Accord. This agreement seeks to encourage countries to take the issue of rising global temperatures seriously. With nearly all countries signing this agreement, many CCTS projects are expected. Pipelines are employed in the transportation of CO2. CO2 fluids contain impurities that affect the fluid properties and flow dynamics, but pipelines are mostly designed assuming that the CO2 fluid is pure. CO2 pipeline fluids contain at least 90 % CO2 with the balance made up of impurities. The impurities include nitrogen, methane, oxygen, hydrogen, sulphur dioxide, hydrogen sulphide, carbon monoxide, ammonia, argon, etc. The effects of the impurities are studied using simulation software; Aspen HYSYS, gPROMS and HydraFlash. The results show that all impurities impacted negatively on transportation. At equal concentrations, hydrogen had the greatest effect on fluid properties and hydrogen sulphide the least impact. At the specified allowable concentration, nitrogen had the worst effect on pressure loss (32.1 %) in horizontal pipeline, density, and critical pressure. Carbon monoxide (with only 0.2-mol %) had the smallest effect in pressure drop (0.3 %). Analysis of supercritical and subcritical (or liquid) CO2 fluid transportation shows that subcritical fluids have higher densities (more volume transported) and lower pressure losses than supercritical fluids. Subcritical fluid transportation would therefore have lower pipeline transportation costs than supercritical fluids. Also, soil heat conductivity has greater effect than ambient temperature in buried pipelines. Simple equations that approximate binary CO2 fluid properties from pure CO2 properties were developed and presented.
    • The Impact of Subjective Factors on Performance Evaluation: The Applied Case of Outsourced Call Centres in Egypt Based on Neural Networks Approach

      Sivarajah, Uthayasankar; Mahroof, Kamran; Perrett, Robert A.; German, Hayley; Ahmed, Abdelrahman M. (University of BradfordFaculty of Management, Law and Social Sciences, 2020)
      The operations efficiency, service quality and resources productivity, are the core aspects of the call centres competitive advantage in massive market competition. Thus, subjective evaluation is the leniency, perception and bias in performance evaluation which impact the efficiency of the operations and leads to frustrated customers. The study aims to determine the subjective performance evaluation in call centres to get a more objective measurement. It can be achieved by identifying factors affecting resources performance evaluation through the development of a conceptual model to reduce or eliminate the effect of subjective factors contained in the performance evaluation. The research approach is based on quantitative methodology through cross-sectional self-reports for 224 participants’ work in eight outsource call centres located in Egypt. The research aims to determine the subjective evaluation factors biases the true performance. It is followed by a machine learning practical application using neural networks for auto-detection the subjective context in the recorded calls to be considered through the evaluation process. The key findings of the study are nine subjective factors out of fifteen that have a direct influence on subjective performance evaluation. The actual performance is the performance evaluation after eliminating the subjective performance. Two different methods have concluded the actual performance. The first method excludes the subjective factors from the resulting evaluation to determine the actual performance. The second method is a prediction model defining subjectivity percent as a call centre baseline for future performance evaluation. Furthermore, the study highlights the potential subjective variables and the degree of influence for each variable. The theoretical contribution is determining the subjective factor and proposing the model to measure and predict the subjectivity in the call centre. The study recommended a restatement for the resource-based theory considering the subjective evaluation effect on performance evaluation. The practical application contribution is based on automating the detection and prediction of subjectivity using a machine learning approach through cascaded Convolutional Neural Networks, which achieved 75% accuracy in classifying the subjectivity for two study constructs: agents and customer behaviour.
    • Understanding The Lived Experiences of Being a Woman Leader in a Technology Organization

      Branney, Peter; Rifet, Saima; Odoh, Anne N. (University of BradfordFaculty of Management, Law and Social Sciences, 2020)
      Purpose: The aim of this study was to explore the experiences of female senior managers in technology organizations and understand how they feel about themselves, their roles and their technology organizations. The study highlights the issues faced by women working in a gendered role, a masculine industry and a non-western, strong patriarchal society. Methodology/Design: A qualitative research methodology was adopted for this study. Eleven semi-structured interviews were used to collect empirical data from women senior managers in Nigerian technology organizations, which was thematically analyzed. Findings: The findings from this study indicate that women in technology are no longer reluctant to progress in this gendered career. Women technology leaders are ambitious and driven to scale the semantic barriers to top management roles. They experience workplace discrimination, insecurities and work-family conflicts, but do not punish themselves for sometimes dropping the ball. Rather, they show up to take on daunting assignments that prove their competence and choose to lead assertively in order to align their core values with the expectations of their role. Research Implications: This thesis makes a contribution to the wider literature on women leaders in technology by providing new insights on the role of patriarchal institutions in technology leadership, from a developing country in Africa. Practical Implications: Practical contributions are to support aspiring women in technology to fine-tune their leadership strategies in order to succeed in this gendered career and become beneficiaries of the vast opportunities in this dynamic industry. For technology organizations, to understand the issues faced by women leaders so that they can support women’s career aspirations by implementing and managing policies that support skilled and high-potential women employees to fulfill their career aspirations, and become change agents at the top management level. These efforts will disrupt stereotypes, change the narrative of inequalities in this industry and improve firm performance. Originality: This study is the first of its kind to focus on the role of patriarchal structures on women leaders’ careers in the technology industry within the context of an African society, which is rare in the literature on women leaders in technology.
    • Assessment and Modelling of Wear prediction and Bit Performance for Roller Cone and PDC Bits in Deep Well Drilling

      Rahmanian, Nejat; Mujtaba, Iqbal M.; Mazen, Ahmed Z.M. (University of BradfordFaculty of Engineering and Informatics, 2020)
      Drilling is one of the important aspects in the oil and gas industry due to the high demand for energy worldwide. Drilling time is considered as the major part of the operations time where the penetration rate (ROP) remains as the main factor for reducing the time. Maximizing ROP to lower the drilling cost is the main aim of operators. However, high ROP if not controlled may impact on the well geometry in terms of wellbore instability, cavities, and hole diameter restrictions. Accordingly, more time is needed for the other operations that follow such as: pool out of hole (POOH), casing running, and cementing. Bit wear is considered as the essential issue that influences in direct way on the bit performance and reduce ROP. Predicting the abrasive bit wear is required to estimate the right time when to POOH to prevent any costly job to fish any junk out to the surface. The two-common types of bits are considered in the research, rock bits (roller cone bits) and Polycrystalline Diamond Compact bits (PDC). This study focuses more on PDC bits because about 60% of the total footage drilled in wells worldwide were drilled by PDC bits and this is expected to reach 80% in 2020. The contribution of this research is to help reducing the drilling cost by developing new tools not to estimating the time when to POOH to surface but also to measure the wear and enhance the accuracy of prediction the bit efficiency. The work is broken down into four main stages or models to achieve the objective: The first stage; estimating of the rock abrasiveness and calculate the dynamic dulling rate of the rock bit while drilling. The second stage; estimating the PDC abrasive cutters wear by driving a new model to determine the mechanical specific energy (MSE), torque, and depth of cut (DOC) as a function of effective blades (EB). The accuracy of the predicted wear achieves 88% compared to the actual dull grading as an average for bits used in five wells. The third stage; modifying the previous MSE tool to develop a more accurate approach; effective mechanical specific energy (EMSE), to predict the PDC bit efficiency in both the inner and outer cone to match the standard bit dulling. The fourth stage; predicting ROP while PDC drilling in hole by accounting three parts of the process: rock drillability, hole cleaning, and cutters wear. The results achieve an enhancement of about 40% as compared to the available previous models. Consequently, the developed models in this study provide a novelty on understanding in more details the bit rock interface process and gain an idea of the relationship between the drilling parameters to enhance the bit performance and avoid damaging the bit. This is basically about optimisation the controllable factors such as: weight on bit (WOB), rotary speed (RPM), and flow rate. The result is the reduction in time losses and the operations cost. To ensure reliability and consistency of the proposed models, they were validated with several vertical oil wells drilled in Libya. The results from the validation of the models are consistent with the real field data. The research concludes that the developed models are reliable and applicable tool for both: to assist decision-makers to know when to pull the bit out to surface, and also to estimate the bit performance and wear.
    • Pentagonal scheme for dynamic XML prefix labelling

      Thakker, Dhaval; Neagu, Daniel; Taktek, Ebtesam A.M. (University of BradfordDepartment of Computer Science, Faculty of Engineering and Informatics, 2020)
      In XML databases, the indexing process is based on a labelling or numbering scheme and generally used to label an XML document to perform an XML query using the path node information. Moreover, a labelling scheme helps to capture the structural relationships during the processing of queries without the need to access the physical document. Two of the main problems for labelling XML schemes are duplicated labels and the cost efficiency of labelling time and size. This research presents a novel dynamic XML labelling scheme, called the Pentagonal labelling scheme, in which data are represented as ordered XML nodes with relationships between them. The update of these nodes from large scale XML documents has been widely investigated and represents a challenging research problem as it means relabelling a whole tree. Our algorithms provide an efficient dynamic XML labelling scheme that supports data updates without duplicating labels or relabelling old nodes. Our work evaluates the labelling process in terms of size and time, and evaluates the labelling scheme’s ability to handle several insertions in XML documents. The findings indicate that the Pentagonal scheme shows a better initial labelling time performance than the compared schemes, particularly when using large XML datasets. Moreover, it efficiently supports random skewed updates, has fast calculations and uncomplicated implementations so efficiently handles updates. Also, it proved its capability in terms of the query performance and in determining the relationships.
    • Computational Face Recognition Using Machine Learning Models

      Ugail, Hassan; Elmahmudi, Ali A.M. (University of BradfordFaculty of Engineering and Informatics, 2021)
      Faces are among the most complex stimuli that the human visual system processes. Growing commercial interest in face recognition is encouraging, but it also turns out to be a challenging endeavour. These challenges arise when the situations are complex and cause varied facial appearance due to e.g., occlusion, low-resolution, and ageing. The problem of computer-based face recognition using partial facial data is still largely an unexplored area of research and how does computer interpret various parts of the face. Another challenge is age progression and regression, which is considered to be the most revealing topic for understanding the human face changes during life. In this research, the various computational face recognition models are investigated to overcome the challenges posed by ageing and occlusions/partial faces. For partial face-based face recognition, a pre-trained VGGF model is employed for feature extraction and then followed by popular classifiers such as SVMs and Cosine Similarity CS for classification. In this framework, parts of faces such as eyes, nose, forehead, are used individually for training and testing. The results showing that there is an improvement in recognition in small parts, such as recognition rate in forehead enhanced form about 0% to nearly 35%, eyes from about 22% to approximately 65%. In the second framework, five sub-models were built based on Convolutional Neural Networks (CNNs) and those models are named Eyes-CNNs, Nose-CNNs, Mouth-CNNs, Forehead-CNNs, and combined EyesNose-CNNs. The experimental results illustrate a high recognition rate when it comes to small parts, for example, eyes increased up to about 90.83% and forehead reached about 44.5%. Furthermore, the challenge of face ageing is also approached by proposing an age-template based framework, generating an age-based face template for enhanced face generation and recognition. The results showing that generated new aged faces are more reliable comparing with state-of-the-art.
    • Hospital and care home nurse perspectives on optimising care for people living with dementia who transfer between hospitals and care homes

      Downs, Murna G.; Blenkinsopp, Alison; Mountain, Gail; Lord, Kathryn; Richardson, Angela (University of BradfordFaculty of Health Sciences, Centre for Applied Dementia Studies, 2020)
      Background: Transitions out of hospital result in poor outcomes for older people. Research investigating transitions for care home residents living with dementia is limited, even though such residents often have multi-morbidities and frequently use hospital services. Nurses are key care providers. Yet their perspectives on optimising care for people living with dementia transferring back to their care home remains under explored. Aims: This qualitative descriptive study explores hospital and care home nurses’ perspectives on how they optimise care for people living with dementia who transfer from hospital back to their care home, and the alignment of this care with best practice. Methods: Thirty-three nurses participated in either semi structured interviews or focus groups. Data were analysed using qualitative content analysis. Results: Nurses described four roles: 1) exchanging information, 2) assessing and meeting needs, 3) working with families and 4) checking and organising medication. They described care home residents with dementia as having distinct needs and variation in how they provided care. Nurses described interdependent roles, but care home nurses were often excluded from involvement in planning resident’s care on return and were not fully recognised as members of wider healthcare teams. Facilitators for optimising care include: nurses understanding the principles of dementia care, nurse leadership and autonomy, having positive relationships between hospital and care home nurses and opportunities for joint working. The care practices nurses described broadly aligned with best practice. Implications: Hospital and care home nurses require joint working opportunities to understand their roles and build relationships. Care home nurses’ status needs to be addressed with action to support their integration into the wider healthcare system.
    • Sustainable Renewable Energy Policy on Energy Indicators, Electric Power and Renewable Energy Supply Chains. A study of renewable energy policies, energy indicators and electrical power distribution

      Carruthers, Andrew; Munive-Hernandez, J. Eduardo; Owaka, Smart O. (University of BradfordFaculty of Engineering and Informatics, 2020)
      Due to the result of the sudden fossil fuels over-night price rises of 1973/1974, coupled with the depletion of the traditional energy resources, many initiatives globally have addressed the efficient use of these resources. Since then, several renewable energy sources have been introduced as alternatives to traditional resources to protect environmental resources and to improve quality of life. Globally, there are more than a quarter of the human population experiencing an energy crisis, particularly those living in the rural areas of developing countries. One typical example of this is Nigeria. This is a country with approximately 80% of her population consistently relying on combustible biomass from wood and its charcoal derivative. Nigeria has an abundant amount of both renewable and fossil fuel resources, but due to the lack of a reasonable energy policy (until recently), it has concentrated on traditional fossil fuels alone. Renewable energy is now Globally considered as a solution for mitigating climate change and environmental pollution. To assess the sustainability of renewable energy systems, the use of sustainability indicators is often necessary. These indicators are not only able to evaluate all the sustainability criteria of the renewable energy sources,1 but also can provide numerical results of sustainability assessment for different objective systems.
    • An Investigation into Human Resource Development (HRD) Needs of Nurses. The Case of Public Health Sector, Pakistan.

      Analoui, Farhad; Shahzad, Rana U. (University of BradfordDepartment of Peace Studies and International Development, Faculty of Management, Law and Social Sciences, 2020)
      The research investigates the health services of Pakistan by exploring current Human Resource Development (HRD) practices and social skills training opportunities for the development of nursing staff. The research aims to explore the best practice in social skills and competency development through HRD activities by detailing a project to identify the learning needs of registered nurses leading to improved quality care services. An exploratory research approach has been adopted to achieve research objectives. This mixed method oriented research, is primarily quantitative case study, supplemented by qualitative interviews to validate and enrich data findings from questionnaires to substantiate the research. The data was collected through 600 questionnaires and 10 interviews from five major public hospitals of Lahore, Pakistan. The research has identified multiple and diverse challenges of inadequate and improper HRD infrastructure, transformational leadership and participative style of management is resulting into degenerating attitudes and negative behaviours thus causing further slump. These counterproductive elements are failing to imbibe positive social skills and abilities in nursing staff resulting in creating impediments in deliverance of quality care services. This clearly indicates that there is no policy in place therefore, based on empirical evidences, as well as critical review of the literature, it proposes a model for achieving critical social skills development through training and development in order to achieve quality care standards based on the broad and long-term perspective of the strategy of input, process, output and outcome to support nursing sector, social skills development in particular to achieve optimum quality care objectives.