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Soft actor critic based deep reinforcement learning for optimization of global maximum power point tracking in PV systems during partial shading conditions
No full textOne of the major challenges in Photovoltaic (PV) systems is the effective tracking of the MaximumPower Point (MPP) during Partial Shading Conditions (PSC). Partial shading occurs when only a portionof the PV array is shaded due to obstacles like trees, buildings, or clouds. One possible result of long term partialshading is the hotspot phenomenon, where the undesirable temperature increase causespermanent damage to the solar cells. The utilization of bypass diodes is a common solution to preventhotspot problems and associated power loss. However, this results in multiple local maxima in thepower voltage curve, making it difficult for traditional Maximum Power Point Tracking (MPPT)algorithms to accurately locate the Global Maximum Power Point (GMPP). Addressing this issue iscrucial for enhancing the overall energy conversion efficiency and reliability of PV systems. Utilizingnovel approaches to improve energy conversion efficiency is crucial in photovoltaic systems andsubsequently lower the costs of PV energy. An efficient MPPT controller which can track the optimumoperating point of the DC-DC converter which in turn ensure maximum power is transferred from thesource to the load during PSC. The research explored the feasibility of employing AI driven strategies toaddress the limitations of traditional MPPT methods controllers during PSC in PV systems. The noveltyof this research is in applying an actor-critic based deep reinforcement learning agent, specifically theSoft Actor Critic (SAC), to detect the global maximum during partial shading. The SAC reinforcementlearning agent replaces the traditional controller and acquires knowledge through its interactionswithin the environment. The proposed Deep Reinforcement Learning (DRL) based approach offersadvantages, including the elimination of the need for real world training data. The SAC agent wasdesigned and trained using MATLAB and Reinforcement Learning (RL) Toolbox. The proposed MPPTcontroller has been designed and tested through simulations in MATLAB Simulink. The proposed DRLMPPT method enhances tracking efficiency to 99.9%, achieving rapid GMP tracking with an averagetracking time of 0.304 seconds and a settling time of 0.14 seconds. The MPPT controller tracked theGMP with minimal oscillations around the Maximum Power Point (MPP), resulting in a steady stateefficiency of 97%. The results demonstrate superior GMP tracking under both static and dynamic PSCscenarios. The SAC MPPT shows a rapid tracking response and minimal oscillations, enhancing systemstability. The SAC MPPT controller improves GMP tracking efficiency compared to traditional and otherAI-based MPPT methods. Furthermore, the results are validated using Hardware in the Loop (HIL)testing, showing good agreement with the simulation outcomes
Large language model based interactive system for medical report analysis
No full textMedical reports can contain technical vocabulary, abbreviations, and technical terms that are barriers to patient comprehension, with impacts on health literacy and decision-making. This article describes the design and evaluation of an AI system to simplify automated medical reports, generate visual aids, and interactive question answering. The system includes OCR for text extraction, NLP pipelines for terminology simplification, and a Q&A module using large language models (LLMs). Three models, ChatGPT, ClinicalBERT, and DeepSeek, were comparatively evaluated on four tasks: term extraction, explanation quality, term-to-image mapping, and relevance in dialogue. DeepSeek performed the best among all models with 0.92 F1-score, 0.84 BLEU, and 88% visual mapping success. A hybrid pipeline integrating BioBERT with generative LLMs improved accuracy by 12% over single-model baselines. Findings indicate that a blend of domain-specific extractors and generative models provides a strong methodology for enhancing patient-focused medical communication
A Great Variety of Morbid Symptoms
No full textThis paper is an invited response to an article in The New Statesman based on an interview with Joe Rollin from the Orgreave Truth and Justice Campaign (OTJC) (Lloyd, 2025). In that article, Rollin reflects on the announcement that a public inquiry will (finally) take place on the violent confrontation between striking miners and police at Orgreave coking plant in June 1984, the so-called Battle of Orgreave – an event which Rollin rightly describes as more of an ambush than a battle. On one hand, this is a significant victory for the OTJC, an organisation which has campaigned long and hard for a public inquiry, even if what happened at Orgreave – and why – is already quite clear. The New Statesman article then deals with the riots of summer 2024, which spread across much of England following the murder of three young girls by the British-Rwandan, Axel Rudakubana. Perhaps the worst of these incidents took place at the Holiday Inn Express, a hotel accommodating asylum seekers on the site of the former Manvers Main Colliery near Wath-upon-Dearne in South Yorkshire, where protestors attempted to storm and then burn down the building, and many who took part were arrested and subsequently jailed
Storying otherwise’ towards care-full writing practices in higher education
No full textIn this paper, ‘storying otherwise’ (Haraway in Terranova, 2016), as a radical act of deliberate experimentation, is utilised to explore care and care-full writing practices in higher education. We think-with care and care-full writing through a posthumanist lens, drawing on an experimental writing session at the European Conference of Qualitative Inquiry 2024. Diffracting the stories that were created in the session, we employ e-zine making as an analysis method to open up different possibilities and new realities. In doing so, care is framed as a creative and sensorial act of connecting across time, prompting us to reconsider what care-full writing might involve. When care becomes an act of connecting with past/present/futures, we make different stories, rememberings and imaginations come to matter in writing. Enacting care creatively by partnering with our environments, materials, and other bodies through experimental and collaborative forms of writing allows care with others to be expressed, shared, explored, and valued differently. And, acknowledging the sensorial experience with/in writing, connecting to what is collectively felt around writing, opens the writing space up to shared experiences that expand collective capacities for engagement. We conclude with suggestions for deliberate and provocative writing spaces that allow those creating academic writing (including students) to engage with the entanglements of past/present/future, material and the sensorial, from which different writing emerges. In doing so, we argue that writing can be an important space for care-full practices in academia.
Investigating the evolutionary dynamics of IT-mediated guanxi in Chinese business practices A comprehensive analysis of digital transformation in B2B relationships
No full textThis research investigates the evolution of guanxi, a traditional Chinese relationship-building system, within the context of digital transformation in business practices. It conceptualises its progression through four stages, including guanxi 1.0, 2.0, 3.0 and 4.0. This conceptualisation shows the stages that guanxi has developed from interpersonal and localised exchange to digitally mediated and globalised relationship. This research especially pays attention to the fourth stage, guanxi 4.0, to discuss “IT-mediated” guanxi, a paradigm where advanced digital technologies, including social media, cloud computing, big data, blockchain and Artificial Intelligence (AI), fundamentally redefine the modes in which guanxi is formed and applied in today’s Chinese business context.The main objectives of this research are to develop a conceptual framework for IT-mediated guanxi, determine its role in developing B2B relationships, and evaluate the organisational effects in the Chinese market. This research bridges between existing Chinese cultural values of trust, reciprocity and mutual benefits, and today’s technological innovation through using Social Capital Theory (SCT) and Relationship Marketing Theory (RMT). This research employs qualitative methodologies, conducting 61 semi-structured interviews to explore how advanced digital technologies are applied to enhance organisational trust, facilitate strategic decision-making, and support inter-organisational collaboration in Chinese ICT, manufacturing and construction sectors.The research results indicate that guanxi 4.0 facilitates real-time and scalable interactions, especially in ICT and manufacturing industries that rely on digital tools to enhance network and efficiency. By contrast, the construction sector is more entrenched in traditional practices and exhibits less integration of IT-mediated guanxi, which reflects this sector’s people-intensive nature.This research makes significant theoretical and practical contributions by conceptualising the stages of guanxi development and integrating cultural heritage and digital innovation in business guanxi practices. In addition to enriching existing literature, this research also presents action strategies that businesses can undertake to leverage IT-mediated guanxi to cope with the complexities of China’s digital economy. The research results highlight the need to adopt a balanced perspective that combines technology innovation with the existing cultural values of guanxi, accommodating organisations’ development of resilience and adaptability in increasingly competitive and globalised markets
Design of combined pile raft foundation (CPRF) under the loads of reactor (containment) and auxiliary buildings of a nuclear power plant
No full textThere have been numerous studies on the designing of a pile raft foundation for nuclear power plants. However, the main focus of this study is the design of pile raft foundations for both containment and auxiliary buildings. The total area of the plant is divided into 4 quadrants where each quadrant is separated by 1m of dilatation. Since there are limited studies on the use of dilatation in pile raft foundations, this paper focused on the effectiveness of dilatation in pile-raft foundations of superstructures. This paper explores the design of five distinct rafts, one for each quadrant of the nuclear power plant, with each foundation section having specific pile arrangements and thicknesses. The central raft for the reactor building bears the highest load and requires thicker reinforcement. Advanced design methodologies were employed, including software like GEO5 software for geotechnical analysis and Tekla Structural Designer for structural modelling. In particular, the paper incorporates pile spacing of 2.5 meters and 5 meters for the containment and auxiliary buildings, respectively, with pile lengths of 20 meters for the containment and 15 meters for the auxiliary buildings. The findings demonstrate that with the combination of pile-raft, the differential settlement can be significantly reduced. The research concludes that dilatation in CPRF design can effectively mitigate the risks associated with foundation movement, ensuring structural integrity and long-term operational safety. Finally, the result of the pile and raft design shows that the total load of 26000 kN will be safely carried by the pile-raft foundation
Factors Influencing FinTech Adoption Among Bank Customers in Palestine: An Extended Technology Acceptance Model Approach
No full textThis study examines FinTech adoption in the Palestinian banking sector, highlighting its role in driving innovation, improving customer satisfaction, and ensuring competitiveness. Using an extended Technology Acceptance Model (TAM) and SmartPLS 4.0 software for structural equation modeling, the research investigates factors influencing FinTech adoption among Palestinian bank customers. Findings show high adoption rates, with nearly half of customers also using non-bank FinTech services. While most prefer FinTech solutions from their banks, many are open to switching providers for better service, convenience, or pricing. Brand strength, trust, and awareness significantly impact perceptions of ease of use and usefulness. Customers trust bank-provided FinTech for precision and reliability but remain concerned about security. A lack of customer awareness highlights the need for targeted educational campaigns. These insights confirm the selection of an extended TAM framework as being an appropriate analytical tool in the Palestinian banking sector, incorporating brand, trust, and awareness alongside ease of use and usefulness. It emphasizes the need for banks to innovate, strengthen security, and enhance awareness efforts to retain and attract customers in a competitive landscape
Enhanced IoT-Based Face Mask Detection Framework Using Optimized Deep Learning Models: A Hybrid Approach with Adaptive Algorithms
No full textThe COVID-19 pandemic has made face mask detection into a big thing because it is essential in public health monitoring. Meanwhile, the growing number of things that can be connected to the internet and the increasing integration of this technology mean that edge devices are now in demand for effective real-time face mask detection models. Often, existing methods require some kind of pre-installed equipment or difficult-to-manipulate environmental conditions, and computational resource constraints essentially put an end to them. In the present study, a hybrid Flame-Sailfish Optimization (HFSO)-based deep learning framework is proposed. It combines the feature extraction capabilities of ResNet50 with the efficiency of MobileNetV2. The HFSO algorithm optimizes crucial parameters such as detection thresholds and learning rates. So that the model can take full advantage of computing capacity and still operate in real time on devices with limited resources. The model was tested on three data sets-Kaggle Face Mask Detection dataset, Public Places dataset, and Public Videos dataset-achieving up to 97.5% accuracy. It outperformed the previous leader in all cases. The results prove that this framework is reliable and easily applicable for identifying people wearing masks under different conditions. However, where there is great occlusion of the face or video feed quality is bad, the model's performance will drop somewhat. Future work should focus on increasing difficulty in detections, broadening the application of this method to other health monitoring systems based on the Internet of Things, and ensuring that its robustness remains unaltered
Alkali-Treated Borassus Husk Fiber Reinforced High-Heat Resistant Epoxy: Insights Into Their Thermal, Dynamic Mechanical, and Outgassing Properties
No full textNatural fibers from renewable resources present a sustainable and biodegradable alternative to synthetic reinforcements. This study explores the thermal and mechanical performance of Borassus husk fiber/epoxy composites, fabricated using a hand layup process with 5% NaOH alkali treatment at varying durations (0.5–2 h). Thermal and thermo-mechanical properties were assessed using thermogravimetric analysis (TGA), dynamic mechanical analysis (DMA) followed by scanning electron microscopy (SEM) analysis, and outgassing tests. Results show that alkali treatment significantly improves the composites' thermal stability, indicated by increased char content (up to 8.11%) and higher integral process decomposition temperature (IPDT), with the 0.75-h treated sample reaching 525°C. The composites also demonstrated enhanced energy dissipation and stiffness compared to neat epoxy (NE) and other natural fiber-based composites. Glass transition temperature (Tg) decreased from 150°C (NE) to 126°C–137°C for treated samples, yet remained higher than those reported for other bio-fiber composites. The 0.75TBHFE sample exhibited the best balance between stiffness and damping, supported by improved phase angle and fiber–matrix adhesion observed in SEM analysis. Outgassing results showed an increase in total mass loss (0.11%–0.53%) compared to NE (0.26%), though still within acceptable limits for thermal stability. These findings highlight the potential of alkali-treated Borassus husk fiber/epoxy composites as high-performance, sustainable materials suitable for aerospace applications. Further research is recommended to address property variability in natural fibers and to develop efficient supply chains for large-scale industrial production