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Education, work and social mobility in Britain's former coalfield communities: reflections from an oral history project
No full textThis paper draws on an oral history project which focuses on former coalminers' experiences of education and training. It presents the stories of five participants, all of whom undertook significant programmes of post-compulsory education during or immediately after leaving the coal industry and achieved a degree of social mobility over the course of their working lives. The paper compares and contrasts their experiences with those which now exist in Britain's former coalmining communities which, it is argued, have been substantively attenuated over time, especially for young men. Whilst it is evident that individual choice and motivation can play an important role in helping (or hindering) young people's journeys through education and employment, the central argument of the paper is that individual labour market success lies at the intersection of structure and agency - although the data presented also demonstrate the extent to which opportunities available to young men in the former coalfields have been diminished by de-industrialisation
Improved acceptance model: unblocking potential of blockchain in banking space
No full textOver the past ten years, blockchain has emerged as the new buzzword in the banking sector. The new technology is being adopted globally in many industries, including the business sector, because of its unique uses and features. However, no adoption model is available to help with this process. This research paper examines the new technology known as blockchain, which powers cryptocurrencies like Bitcoin and others.It looks at what blockchain technology is, how it works especially in the banking sector, and how it can change and upend the financial services sector. It outlines the features of the technology and discusses why these can have a significant effect on the financial industry as a whole in areas like identity services, payments, and settlements in addition to spawning new products based on things like "smart contracts". The adoption variables found in the literature study were used to gather, test, and evaluate the official papers that are currently available from regulatory organizations, practitioners, and research bodies. This study was able to classify adoption factors into three categories—supporting, impeding, and circumstantial—identify a new adoption factor, and determine the relative relevance of the factors. Consequently, an institutional adoption paradigm for blockchain technology in the banking sector is put out. In light of this, it is advised to conduct additional research on using the suggested model at banks using the new technology in order to assess its suitability
Advancing Behavioural Dynamics in Africa’s Banking Sector; Using Employees of Nigeria as a case study
No full textThe ongoing advancement of the Internet has facilitated the development of newapplications and enterprises, which have become essential across various sectors,including finance, commerce, governance, communication, education, research, andinnovation. In Nigeria, the Information Communication Technology (ICT) sector issignificantly reshaping financial institutions, particularly within the banking sector.However, as banks advance and refine their services, there is a concurrent rise inglobal cybercrime, leading to substantial financial repercussions across Africa. Thissituation has positioned information security as a critical concern, necessitatingsophisticated strategies that encompass technical and behavioural dimensions,including the roles of individuals (people), processes, and technology.This thesis focuses on advancing information security behaviour within Nigeria'sbanking sector by leveraging the concept of Information Security Culture (ISC). Themain objectives are to assess the current state of Information Security Culture, identifykey elements that foster a robust security culture, develop a conceptual framework,and offer practical recommendations to improve security behaviours among bankingemployees.The thesis employed a mixed-methods approach, integrating qualitative andquantitative analyses. In this thesis, a thorough review of existing literature wasconducted to identify research gaps, it revealed the insufficient attention given tomulticultural contexts in Africa, the neglect of the ‘human factor’, and an excessivedependence on technological solutions. It evaluated the present landscape ofinformation security in Nigeria and underscores the necessity for a mixed-methodsapproach. The research utilized existing literature, internal documents from banks inNigeria, and ISO/IEC 27001:2013 standards to formulate research hypotheses,interview questions, and survey instruments. For quantitative approach, Participantswere chosen through probability sampling and completed questionnaire utilizing a 7-point Likert scale. Data preparation included addressing missing values andperforming normality assessments. The reliability of the data was evaluated usingCronbach's alpha and composite reliability measures. The CFA methodology wasemployed for the analysis of the measurement model, focusing on aspects such asconvergent validity, discriminant validity, and goodness-of-fit assessments. Theevaluation of construct fitness was conducted through various goodness-of-fit indices,while hypothesis testing was carried out by examining path coefficients and P-values.To gather qualitative data, semi-structured interviews were performed utilizing quotasampling, and the data were subsequently analysed using thematic analysis.Triangulation techniques were applied to synthesize and present the researchoutcomes. The thesis findings offer a comprehensive analysis of the informationsecurity landscape within Nigeria's banking sector, underscoring several criticalaspects that influence the effectiveness of security practices. A key observation is thefundamental role that a security-oriented organizational culture plays in enhancinginformation security. When security values are deeply embedded within theorganizational culture, employees are more likely to adhere to security policies andexhibit proactive security behaviours. This integration of security into the cultural fabricof the organization fosters a shared responsibility for security across all levels, fromleadership to operational staff.Leadership commitment emerged as a pivotal factor in shaping and maintaining arobust information security culture (ISC). The active involvement and visible supportfrom top management are essential in promoting a security-conscious environment.Leaders who prioritize information security and visibly back security initiatives createa culture of compliance and vigilance among employees, thus reinforcing the overallsecurity posture of the organization.Ethical practices also play a significant role in information security, as the researchhighlights the strong connection between ethics and security compliance. Employeeswho uphold high ethical standards are more likely to follow security protocols andreport potential breaches. This underscores the importance of incorporating ethicaltraining into broader security education efforts, emphasizing that ethical behaviour isintegral to effective information security.Continuous employee training emerged as another critical component in sustainingand improving security behaviours. Regular, targeted training programs are vital forkeeping employees informed about the latest security threats and best practices. Thisongoing education helps reduce the likelihood of human error, a major contributor tosecurity incidents, by ensuring that employees remain vigilant and knowledgeable.The thesis further emphasized the importance of addressing human factors in security,recognizing that security is not solely a technical issue but also a behavioural one.Personal beliefs, attitudes, and motivations significantly impact security outcomes.Therefore, tailored behavioural interventions that address these human factors arecrucial for enhancing the overall security posture of banks.Effective risk management practices are highlighted as essential for identifying andmitigating potential security threats. This thesis revealed that banks that integrate riskmanagement into their daily operations, including regular security assessments andaudits, are better equipped to respond to emerging threats. This proactive approachis key to preventing security breaches and minimizing their impact, demonstrating theimportance of a structured risk management framework within the banking sector.Compliance with international standards, particularly ISO/IEC 27001, was identified asa critical component of successful information security strategies. Banks that aligntheir practices with these standards demonstrate a higher level of security maturityand resilience against cyber threats. Adherence to such standards not only enhancessecurity but also provides a benchmark for continuous improvement in securitypractices.Cultural diversity within the workforce was also found to be a significant factorinfluencing security behaviours. In a multicultural context like Nigeria, understandingand addressing the diverse cultural perspectives within the organization is vital forimplementing effective security measures. This finding highlighted the need forculturally sensitive security policies and training programs that consider the variedcultural backgrounds of employees, ensuring that security practices are inclusive andeffective across the board.Contributions of this research include the development of a conceptual framework thatintegrates key elements of ISC, employee behaviour analysis, and compliancemetrics. This framework offers a comprehensive approach to improving informationsecurity behaviour in the banking sector of Nigeria, providing both academic andpractical insights. Additionally, the research bridges a significant gap in the literatureby focusing on behavioural information security in a multicultural African context, whichhas been largely underexplored.Recommendations for the banking sector emphasize the need for continuousemployee training programs that address the human element of security,strengthening organizational culture to prioritize security, and implementing regularassessments of security practices aligned with international standards. It alsoadvocates for the adoption of a proactive approach to risk management, ensuring thatsecurity strategies evolve in response to emerging threats.Future research paths are identified based on the thesis' limitations. These include theneed for further exploration of ISC in other sectors beyond banking, the impact ofcultural diversity on security behaviours in African countries, and the development oftailored security strategies that address specific regional challenges. Additionally,longitudinal studies could provide deeper insights into how ISC evolves over time andits long-term impact on security outcomes.Key differences between this thesis and other research in the field include its focus ona multicultural African context, which has been relatively neglected in existing studies.While previous research has often emphasized technical solutions, this thesishighlights the importance of integrating behavioural and cultural dimensions intoinformation security strategies. The thesis’ use of a mixed methods approach alsoprovides a more comprehensive understanding of ISC, combining quantitative rigorwith qualitative depth to offer actionable insights for both practitioners and scholars.In summary, this thesis advances the understanding of behavioural informationsecurity within a multicultural framework, offering a conceptual framework andpractical recommendations to improve security practices in Nigeria's banking sector.The findings have significant implications for policymakers, industry leaders, andacademics addressing cybersecurity challenges in developing economies, particularlyin Africa
Hybrid deep learning approach for age and gender classification from iris images
No full textThis paper presents a novel hybrid deep learning model that combines Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) for accurate age and gender classification from iris images. Using the GMBAMU-IRIS dataset, the model leverages CNNs for spatial feature extraction and RNNs for sequential pattern recognition. The proposed model achieved an age classification accuracy of 85.68% and a gender classification accuracy of 98.95%, outperforming traditional methods. These findings highlight the potential of hybrid models in enhancing biometric recognition systems. 1 Introduction Biometric recognition systems have emerged as critical components in various security and authentication applications, providing reliable and efficient means of identifying individuals based on their physiological and behavioral traits. Among the array of biometric modalities, the human iris stands out due to its unique patterns and remarkable stability throughout an individual's life. Iris recognition systems leverage the distinct textural patterns within the iris to achieve high levels of accuracy and reliability in personal identification and verification tasks [1][2]. Beyond the primary goal of identification, there is a growing interest in using iris images for soft biometric traits, such as age and gender classification. Accurate age and gender classification can significantly enhance the functionality of biometric systems by providing additional contextual information [3]. This additional layer of data can improve user experience , enable demographic-specific applications, and enhance the robust-ness of security systems by adding another factor of authentication [4]
A Virtual Reference Point Kinematic Guidance Law for 3-D Path-Following of Autonomous Underwater Vehicles
No full textThis work presents a novel method for 3-D path-following and path-tracking of AutonomousUnderwater Vehicles (AUVs) using the concept of a Virtual Reference Point (VRP) and a kinematic guidanceprinciple. The origins of the along-, cross- and vertical-track errors are proven globally exponentially stable(GES) using Lyapunov stability analysis. The kinematic guidance law exploits the design flexibility of auser-defined VRP in conjunction with a feedback linearizing controller. In addition, a novel concept calledthe Handy Matrix is introduced and applied to shape the kinematic equations such that the AUV’s nonactuated degrees of freedom (DOFs) can be controlled in a 3-D path-following scenario. The case studyconsiders the Remus 100, a torpedo-shaped underactuated AUV, performing a 3-D path-following maneuver.The computer simulations show that the kinematic guidance law shows excellent tracking performance andstability even in the presence of ocean currents and white measurement noise
An improved deep learning unsupervised approach for MRI tissue segmentation for Alzheimer's Disease Detection
No full textAlzheimer's disease (AD) ranks as the sixth leading cause of death, emphasizing the need for early-stage prediction to prevent its progression. Due to the complexity and heterogeneity of medical tests, manually comparing, visualizing, and analyzing data is often difficult and time-consuming. As a result, a computational approach for accurately predicting brain changes through the classification of magnetic resonance imaging (MRI) scans becomes highly valuable, though challenging. This paper introduces a novel method for diagnosing the early stages of AD by utilizing an efficient mapping technique to differentiate between affected and normal MRI scans. The approach combines a hybrid unsupervised learning framework, specifically the adaptive moving self-organizing map (AMSOM) method integrated with Fuzzy K-means. To ensure optimal feature extraction, we introduce a hybrid learning framework that embeds feature vectors in a subspace. The analysis compares various mapping approaches to identify features linked to Alzheimer’s disease. The proposed method achieves a classification accuracy of 95.75% on the Open Access Series of Imaging Studies (OASIS) MRI brain image database, outperforming existing methods
Introduction
No full textAbstract
The aim of this chapter is to introduce the aims of the book, how it is structured and introduce the main concepts of positive psychology and positive education. This includes a brief history of positive psychology and how it led to its application in schools as positive education. The chapter introduces positive education, what it is, why wellbeing is important in education and some of the main frameworks for positive education being used in schools. A rationale for why the focus of this book is on positive education and at all levels of those involved in education in the UK is also provided. Namely, to address whether positive education is too positive for the UK (Robson-Kelly, 2018)
EL-RFHC: Optimized ensemble learners using RFHC for intrusion attacks classification
No full textThe extensive growth of mobile technology leads to magnifying the usage of digital gadgets around the world. This requires a fast-interconnecting communication medium to transfer the data between the devices. Meanwhile, the intruders attempt to make huge traffic in the network that leads to loss of data. To identify the intrusion attacks, ensemble Machine Learning (ML) classifiers are applied using the various feature variables importance. However, most of the transmitting data contains high dimensions with numerous variables leads to more execution time to classify the attacks. This study initiated the novel approach fusion of the Random Forest classifier and High Correlation (RFHC) feature selection approach to diminish the quantity of the variables. Also, the count of intrusion attacks class is lower than the normal class leads to generating an imbalanced dataset. Hence, Synthetic Minority Over-Sampling Technique (SMOTE) is suggested to create a balanced dataset for multi-class classification, and Un-upsampled data for binary-class classification respectively. The pre-processed dataset fed into the ensemble machine learners, and attention mechanism-based LSTM to classify as various intrusion attacks and normal data. This research work focused on reducing the CICIDS2017 dataset?s variable dimensions from 71 to 34 using RFHC. The performance results showed that RF classifier performed better with accuracy of 99.4 %, precision 99.4 %, average recall 99.2 % and average F1-score 99.6 % in binary-class classification, and Extreme Gradient Boosting (XGBoost) achieved better accuracy of 99.7 %, precision 98.7 %, average recall 99.5 % and average F1-score 99.2 % in multi-class classification
Evaluation of venous thromboembolism risk assessment models for hospital inpatients: the VTEAM evidence synthesis
No full textBackground: Pharmacological prophylaxis during hospital admission can reduce the risk of acquired blood clots (venous thromboembolism) but may cause complications, such as bleeding. Using a risk assessment model to predict the risk of blood clots could facilitate selection of patients for prophylaxis and optimise the balance of benefits, risks and costs.Objectives: We aimed to identify validated risk assessment models and estimate their prognostic accuracy, evaluate the cost-effectiveness of different strategies for selecting hospitalised patients for prophylaxis, assess the feasibility of using efficient research methods and estimate key parameters for future research.Design: We undertook a systematic review, decision-analytic modelling and observational cohort study conducted in accordance with Enhancing the QUAlity and Transparency Of health Research (EQUATOR) guidelines.Setting: NHS hospitals, with primary data collection at four sites.Participants: Medical and surgical hospital inpatients, excluding paediatric, critical care and pregnancy related admissions.Interventions: Prophylaxis for all patients, none and according to selected risk assessment models.Main outcome measures: Model accuracy for predicting blood clots, lifetime costs and quality-adjusted life-years associated with alternative strategies, accuracy of efficient methods for identifying key outcomes and proportion of inpatients recommended prophylaxis using different models
Feasibility and preliminary efficacy of metacognitive therapy for health anxiety: A pilot RCT
No full text•We evaluated the feasibility of delivering MCT for health anxiety and to collect pilot data on the treatment's preliminary efficacy as measured by the whiteley index.•MCT was found to be feasible and acceptable for individuals with health anxiety, with clinically significant changes and large effects (Hedges’ g = 3.18).•The results support continued evaluation of MCT in health anxiety and a large-scale randomised trial is supported.
Health anxiety is a pervasive mental health condition, in which people worry about having or developing a serious illness or disease. Cognitive behavioural therapy (CBT) is currently considered the most researched psychological treatment for health anxiety, although several systematic reviews and meta-analysis have shown mixed findings for its efficacy. More efficacious interventions that can be easily integrated within services are required. An alternative to CBT, that has proven more effective in some other disorders, is metacognitive therapy (MCT). The aim was to evaluate the feasibility of delivering MCT for health anxiety and to collect pilot data on the treatment's preliminary efficacy.
Twenty participants with health anxiety were recruited to an open randomized feasibility trial and randomized to MCT or waitlist control. Acceptability and feasibility of MCT was based on recruitment rates, withdrawal, and drop-out, number of MCT sessions attended, completion of questionnaires, and any adverse reactions observed. The study was also used to evaluate initial treatment effects.
MCT was found to be feasible and acceptable for individuals with health anxiety. Recruitment and retention of all participants was high, and no adverse events were observed in either group. Pre to post between group effect sizes on the primary outcome measure The Whiteley Index (Pilowsky, 1967) were large (Hedges’ g = 3.18-Mdiff= 26.2, [95 % CI=18.7–33.6]) in favour of MCT. Clinically significant recovery rates were 80 % at post treatment and follow up.
The results suggest that a trial of MCT was acceptable and feasible in individuals with health anxiety and the treatment effects were statistically significant in comparison to the waiting list. Based upon the design used in this study MCT should be compared with active treatments such as medication, treatment as usual or specific cognitive behaviour therapy protocols in a future definitive randomised trial