Integrated Intrusion Detection And Prevention Model For Moodle Learning Management System

This study developed and evaluated an integrated intrusion detection and prevention (IDP) model for Moodle LearningManagement System (LMS), utilizing Snort 3, Open-Source Security (OSSEC), ModSecurity, and Moodle's securitysettings. The increasing security threats facing LMS platforms was addressed in the study by leveraging the strengths ofeach tool: Snort 3 for network-level detection, OSSEC for host-based monitoring, ModSecurity for web applicationprotection, and Moodle’s native security features for enhanced control. An experimental approach was adopted,beginning with a literature review to identify vulnerabilities, followed by system design, tool configuration, andintegration. The model was tested against simulated attacks, with performance measured by detection accuracy. Theresults demonstrated the model's effectiveness in identifying and mitigating common security threats within Moodle LMSsuch as distributed denial of service, brute force attack, SQL injection and aggressive scan. The study concludes byrecommending the deployment of the IDP model in a live environment for both private/individual owned and publicowned Moodle platforms, for the provision of a robust framework for enhancing security. This work contributes to thebroader field of LMS security through the provision of a comprehensive, multi-layered approach to protectingeducational platforms from cyber threats

The Anatomy of Dark Leadership: A Critical Analysis of Bashar al-Assad's Regime and Its Psychological Impact on Syrian Governance and Society

Bashar al-Assad's regime in Syria has been widely analysed for its authoritarian control, coercive governance, and psychological manipulation. This study critically examines dark leadership characteristics within Assad's rule, mainly through narcissism, Machiavellianism, and psychopathy. It explores how Assad's leadership has manipulated political institutions, repressed opposition, and weaponised propaganda to maintain power, alongside the psychological and social consequences on Syrian society. This research uses qualitative research to incorporate political discourse analysis, thematic analysis of testimonies, and comparative studies of authoritarian regimes. The findings suggest that Assad's leadership has eroded political institutions, instilled long-term psychological trauma, and fragmented Syrian civil society. Additionally, the international community's response to Assad's rule has been inconsistent, reflecting broader challenges in addressing authoritarian leadership and human rights violations. This study contributes to political psychology, governance studies, and international relations, offering insights into the mechanisms of dark leadership and the challenges of dismantling authoritarian structures. The findings provide policy recommendations for rebuilding governance structures, addressing collective trauma, and mitigating the effects of autocratic rule in post-Assad Syria

HALOGrid–HyperAdaptive Long Short Term Memory Model with Intelligent Grid Optimization

HALOGrid is an adaptive edge–cloud malware detection framework for IoT traffic. The approach couples a lightweight LSTM (residual paths, attention, drift-penalty regularization) for low-latency edge inference with a telemetry-driven tuner that performs real-time hyperparameter updates. The tuner employs Augmented Grid Search (AGS): a stage-wise coarse-to-fine exploration with stochastic perturbations, early-stopping of inferior candidates, validation-weighted corrections, and expectation-weighted deployment. A resynchronization controller blends edge and cloud states using divergence- and delay-aware gating; updates are secured via mTLS transport and signed artifacts with rollback. The pipeline integrates preprocessing, drift estimation over multi-metric streams, adaptive learning-rate/regularization adjustment, and A/B deployment safety. Evaluation on CICIoT2023 reports 98.74% accuracy, 1.21% false positive rate, and 12.8,ms mean inference latency on Jetson Nano; energy consumption averages 52.5,mJ/inference. Compared with SGM, HPAI, DFN, ODMS, MIHT, AIMO, IEMS, and DOFD, HALOGrid maintains higher detection fidelity with lower tuning overhead through AGS and secure edge–cloud refinement

Integrated Particle Filter Approach for Enhanced Indoor Robot Localization Using Multi-Sensor Fusion

Mobile robots are increasingly used in rescue missions, household cleaning, and food service due to their stability and affordability. These robots require accurate positional data from sensors, environmental maps, and path-planning algorithms for effective navigation. The objective of this research paper is to present a novel approach to indoor robot positioning that integrates Particle Filter (PF) with Adaptive Particle Filter (APF) methodologies. The proposed system combines data from multiple sensors, including a Laser Range Finder (LRF), dual en-coders, and a gyroscopic unit, to enhance positional accuracy. By processing LRF measurements alongside reflected beacon signals, an algorithm is developed that dynamically adjusts particle distributions for improved localisation. Experimental results show that this integrated approach achieves an accuracy improvement of 96.5% as compared to traditional methods, demonstrating its potential for robust indoor navigation applications

Palmyra Palm Shell (Borassus flabellifer) Properties Part 2: Insights Into Its Thermal and Mechanical Properties

Advancements in modern engineering design require materials that maintain thermal and mechanical stability under diverse conditions. To promote sustainability and eco-friendliness, researchers are increasingly exploring natural alternatives to synthetic fibers. Among bio-fibers, Borassus flabellifer fruit shell (husk), has no other uses than disposal or waste-to-energy in Bangladesh. While other parts of the plant, such as, the fruit and leaf stalks, are commonly utilized for fine and coarse fibers, the husk fiber remains underexplored. Hence, this study investigates exclusively the thermal properties of untreated Borassus husk fibers according to ASTM E2550 and ASTM E1269-11 standards and evaluates their curved specimens' mechanical properties using ASTM D2344 and ASTM D6415 standards. The findings reveal that raw Borassus husk fibers exhibit remarkable thermal stability, characterized by a higher char content and an elevated integral process decomposition temperature compared to the its fine and coarse fibers. During cellulose decomposition, the husk fibers demonstrate a specific heat capacity of 1.6 J/g°C, which surpasses that of coconut fibers. Additionally, mechanical testing indicates that the curved husk possesses competitive inter-laminar tensile strength and short-beam strength, comparable to glass fiber-reinforced polymers, curved woven glass/polyester composites and some bio-composites. Fracture surface analysis reveals a unique morphology, featuring non-uniform, cross-linked, and porous tubular structures, which contribute to the material's distinct thermal and mechanical properties. These results highlight the potential of untreated Borassus husk fibers as a viable material for engineering applications. Utilizing this underexplored resource could promote the cultivation and preservation of B. flabellifer trees, thereby encouraging sustainable development

Ethical Implications of WannaCry: A Cybersecurity Dilemma

The WannaCry ransomware attack of May 2017 marked a critical turning point in cybersecurity history, prompting profound ethical discussions about software vulnerability management. This comprehensive analysis examines the ethical dimensions of the WannaCry incident, focusing on the responsibilities of government agencies, technology companies, and security professionals in handling zero-day vulnerabilities. The study investigates the complex balance between national security interests and global cybersecurity while proposing ethical frameworks for future practice. Through detailed examination of the attack's global impact and subsequent incidents, we demonstrate the ongoing relevance of lessons learned from WannaCry to contemporary cybersecurity challenges

Reducing Landfill Solid Waste To Mitigate The Greenhouse Gases Emissions Towards Environmental Sustainability: A Case Study From Ajman-UAE

Landfills have significant environmental and social impacts due to their associated greenhouse gases (GHGs) emissions. This paper examines solid waste management using Ajman-United Arab Emirates as a case study. It emphasises the necessity of having waste assessment integrated with air quality assessment to monitor and regulate waste disposal procedures The paper examines waste accumulation, previous treatments & services provided at the Ajman landfill. Forecasts of waste accumulated at the landfill indicate a serious issue that needs immediate action from Ajman Municipality despite the low percentage of treatments currently performed. It was found that GHGs increased between 2017 and 2023, with a decrease in 2020 due to COVID-19. Additionally, the paper proposes an integrated waste management model that can reduce landfill-associated GHG emissions and their negative impact on the environment. Moreover, the research predicted that by 2035, Ajman will be able to handle 250,000 tons of waste per year. Moreover, it was indicated that Ajman's environmental trajectory can be improved significantly by capping the landfill

Specialist mental health crisis centres in England: a step forward or a stumble in the dark?

The recent proposal by NHS England to establish specialist mental health crisis centres has prompted considerable discussion. This editorial examines the initiative, which aims to reduce accident and emergency pressure and provide tailored care. However, it raises significant questions about the potential to exacerbate systemic fragmentation. Concerns highlight inadequate funding, the risk of resegregation of mental health from physical care and increased stigma if not properly integrated. This article argues that true holistic care requires seamless integration, advocating strongly for co-located mental health and medical emergency departments, which have shown improved outcomes. Ultimately, the success of these centres depends on addressing wider NHS issues, robust evaluation and a comprehensive vision prioritising the entire mental health pathway, from prevention to long-term recovery, to genuinely transform patient lives

Building AI-Literate Management Graduates: A Multi-Stakeholder Approach

The increasing integration of Artificial Intelligence (AI) in education and business necessitates the development of critical AI literacy among management graduates. This paper explores how institutional policies, pedagogical strategies, and primary stakeholder engagement can support the responsible use of Generative Artificial Intelligence (GAI) in management education. By analysing existing AI literacy frameworks and institutional practices, the study identifies key gaps and proposes a co-designed AI literacy model tailored for institution ‘A’. Using co-design as a central tenet, the study advocates for AI literacy initiatives that align institutional resources with learner needs and professional domains

'Living with Covid': Well-being, Burnout, and Moral Injury in England's Adult Social Care Workforce - A Survey Study

Context: The COVID-19 pandemic presented unprecedented challenges for the adult social care sector, necessitating rapid changes in service delivery. Understanding the factors influencing the well-being of staff beyond the pandemic’s initial crisis response phase is crucial. Objective: The article examines the mental well-being, burnout, and the morally injurious experiences of the adult social care workforce in Greater Manchester during the UK’s ’Living with COVID’ phase, initiated in February 2022. Methods: An online survey collected responses from 251 social care staff. Regression analyses, employing a job-demands and resources framework (JD-R), considered demographic, occupational, and COVID-19-related factors to predict psychological outcomes. Findings: Significant levels of low mental well-being (34%) and burnout (31% likely experiencing burnout, 36% at risk) were observed. Additionally, 40% reported experiencing events that were potentially morally injurious. COVID-19-related factors had a significant impact on these outcomes. Satisfaction with infection control measures and access to sufficient resources were associated with more favourable outcomes. Considerable changes in daily activities and dissatisfaction with infection control measures were associated with increased levels of burnout and exposure to morally injurious experiences. Demographic and occupational factors had a lesser influence. Limitations: The study was conducted in a single geographic region of England with non-probability sampling methods and recruitment, potentially impacting the generalisability of the findings. Implications: The findings highlight the importance of adequate resources and infection control measures in reducing harm in the adult social care workforce and building resilience for future sector pressures