System automation and organisation for intelligent electricity networks

The transition from conventional energy generation to clean energy generation based onrenewable energies is leading to a rapidly growing share of decentralised energy sources in theelectricity supply. As a result, fundamental changes in the electricity supply structure are takingplace, creating new challenges for the decentralised operation of future electricity grids. TheClustering Power Systems Approach (CPSA) provides a solution in terms of the organisationand subdivision of the electricity grid by allocating cluster areas for its structured automationand control. This research focuses on providing a suitable software system for decentralisedautomation and control systems based on the CPSA to meet the rapid changes and futurechallenges in electrical power networks.Using this approach, a developed software architecture design for automation and controlsystems, the so-called Smart Grid Cluster Controller (SGCC), was developed and is presentedin this doctoral thesis. A suitable method for digitally describing the structure of powernetworks and the data organisation of clustered power system status was researched, developedand validated under real grid operating conditions. The topology of decentralised power gridsis mapped by graph-based fundamental structures and enhanced by a novel Neighbour ClusterOverlapping Method (NCOM). In addition, a time-series database was used for decentralisedprocess data mapping, whereby a direct reference to the topology description was realised.Decentralised neighbouring grid cluster areas can be coordinated concerning the necessaryprocess data exchange.The results of the validated software architecture design, the graph-based cluster topologydescription using NCOM, and the organisation for decentralised process data exchange show asignificant contribution to conventional industrial automation systems for the application ofdecentralised automation and control. The results developed based on the research discussed inthis thesis provide the possibility of an organised and structured operation of increasinglydecentralised power networks

An investigation of the impact of Islamic microfinance on women's entrepreneurship development in rural areas of Bangladesh a case study of indigenous women in Chittagong

Islamic microfinance presents a promising solution for fostering women's entrepreneurship and alleviating poverty in emerging economies. This study examines the impact of Islamic microfinance (IMF) on tribal women in Bangladesh, exploring how it aids them in developing entrepreneurial initiatives. Furthermore, it seeks to investigate the effects of Islamic microfinance on tribal women's financial empowerment, the well-being of their families, poverty reduction, and access to economic resource schemes.This study utilises qualitative data collection methods to assess the impact of Islamic microfinance in achieving its objectives. Additionally, this investigation conducts semi-structured interviews with successful tribal women entrepreneurs and those aspiring to entrepreneurship. The interviews encompass two focus groups: effective tribal women entrepreneurs with at least one year of experience, and individuals who have recently participated in or are interested in entrepreneurial programmes and training to engage in entrepreneurial schemes through the Islamic microfinance sector in the future. The qualitative data is analysed through thematic analysis and coded using NVivo software.Furthermore, this thesis evaluates the impact of Islamic microfinance on tribal women's entrepreneurship development in rustic regions of Bangladesh, where there is a shortage of understanding regarding Islamic microfinance facilities. It determines how Islamic microfinance approaches can improve tribal women's entrepreneurship, increasing their contribution to household income and family welfare. In addition, it measures the extent to which Islamic microfinance approaches significantly contribute to expanding the entrepreneurial activities of tribal women. Based on empirical outcomes, the study has highlighted that Islamic microfinance programs contribute considerably to tribal women’s entrepreneurship development and poverty elimination. The research findings also underscore that, through the effective support of Islamic microfinance, tribal women entrepreneurs have contributed to women's empowerment, gender equity, household well-being, and economic enfranchisement in developing countries like Bangladesh.However, the empirical outcomes also have emphasised that tribal women entrepreneurs can succeed better if IMFIs offer them entrepreneurial schemes tailored solely for tribal women, easier access to finance, and formal entrepreneurship training. Finally, these empirical outcomes have contributed to the broader Islamic microfinance literature by reviewing Bangladesh's moderately less investigated emerging economy. This thesis also theoretically and methodologically explores Islamic microfinance's impact and influence on rural women's entrepreneurship development, specifically among tribal women in Chittagong, Bangladesh

The association of compassion and positive psychology among people who offend: a scoping review of the literature

PurposeGlobal recidivism rates remain high, with re-offending being a common issue. Traditional offender rehabilitation programmes often rely on the risk-need-responsivity model and cognitive behavioural therapy. However, the emergence of positive psychology and strengths-based approaches, such as the good lives model and desistance-based approaches, have started to challenge this dominant model, offering alternatives for reducing re-offending. Despite growing interest, the literature on positive psychology and compassion-based approaches in offender rehabilitation is still limited. This paper aims to explore the existing literature and assess its impact on offender populations.Design/methodology/approachA scoping review was conducted, which initially identified 925 articles. After removing duplicates and applying eligibility criteria, 46 articles were included in the final analysis.FindingsFour key themes emerged: the effects of compassion and positive psychology on emotions and traits, the role of relationships and identity, the connection between compassion and desistance, and the protective role of strengths in personal growth and reducing offending. The review underscores the potential benefits of integrating compassion and positive psychology into offender rehabilitation. However, the existing research is sparse, and further studies, such as randomised controlled trials or longitudinal research, are necessary to establish the long-term effects of these interventions on recidivism. Incorporating these approaches could signal a paradigm shift towards a more holistic, human-centred approach to offender rehabilitation.Originality/valueTo the best of the authors’ knowledge, this is the first review to explore both compassion and positive psychology-based interventions among people who offend

Automated Infrastructure Sustainability Assessment: A Deep Learning Approach For Real-Time CO2 Image Analysis

This study investigates the potential of using deep learning for real-time image analysis in assessing sustainable infrastructure and urban development. Convolutional Neural Networks (CNNs) are implemented to evaluate live-captured building images, enabling automated classification and data extraction for decision-making. The proposed approach overcomes the limitations of existing methods by facilitating real-time analysis and large-scale data processing. A dataset exceeding 12,000 images rigorously evaluates the CNN model's performance. This research establishes a framework for leveraging deep learning for real-time assessment of sustainable infrastructure, paving the way for improved data-driven urban planning and development decision-making. The study confirms that the Inception Net V3-based feature extraction technique accurately classifies images based on CO2 emission levels. This classification task is best performed using the Neural Network model. Advanced feature extraction techniques are essential for improved environmental image classification

Learning technology standards development - planning for an improved process and product

This paper presents a framework for improving the legitimacy of learning technology standards by focussing on a better process and product. It is suggested that there is a need for a change in the standardisation paradigm, moving from monolithic to more modular standards

Collective Violence, Strengths, and Perceived Posttraumatic Growth: A Scoping Review

Collective violence—such as armed conflict, state-sponsored violence, and terrorism—represents a profound form of trauma, which can harm individuals, communities, and societies. Existing research has largely examined risk factors and negative psychosocial outcomes from collective violence, neglecting the potential for survivors to draw upon a range of strengths that may allow them to perceive benefits from their experiences, known as posttraumatic growth (PTG). This scoping review uses the resilience portfolio model to highlight a potential portfolio of meaning-making, regulatory, and interpersonal-ecological strength-based resources and assets that are conducive to perceived PTG (PPTG) and possible better functioning following collective violence. The present review identified 52 papers from CINAHL, MEDLINE, PsycArticles, and PsychInfo, spanning from January 1995 to May 2023, which specifically focused on strengths and PTG in populations who reside (or had resided) in over 20 countries. This review highlights individual- and group-level meaning making, regulatory, and interpersonal strengths used by survivors in both individualistic and collectivist societies, providing a more comprehensive understanding of resilience and PPTG after collective violence. Some strengths, such as religious coping, positive reappraisal, and social support, demonstrated mixed relations with PPTG. The research also identified previously uncategorized ecological/systemic supports for PPTG such as political climate, access to education, and sanitation infrastructure, which require more research. The findings call for culturally sensitive approaches that recognize and promote individual and community efforts to enhance well-being among populations disproportionately affected by collective violence

Dynamic Mechanical Analysis of Borassus Husk Fiber Reinforced Epoxy: Evaluating Suitability for Advanced Aerospace and Automotive Applications

This study investigates the effect of elevated temperatures on the mechanical properties of Borassus husk fiber‐reinforced epoxy composites, focusing on their potential for aerospace internal structural components. Composites were fabricated using Borassus husk fibers incorporated with epoxy resin, including 5% alkali‐treated fibers (treated for varying durations) to improve adhesion. Dynamic Mechanical Analysis (DMA) was performed according to ASTM D5418‐01 standards. Results revealed that both untreated and alkali‐treated fibers enhanced the storage modulus of the composites. The highest loss modulus was observed for the composite with 1‐h treated fibers. The glass transition temperature ( T g ), determined from the peak loss modulus, was significantly higher (84°C–89°C) for treated Borassus husk fiber/epoxy composites compared to neat epoxy and composites reinforced with other natural fibers, such as flax, jute, palm sprout, date palm, sisal, and kenaf. Alkali treatment also notably increased the tan δ (damping factor), with the highest value (1.2) for the 0.75‐h treated fiber composite, outperforming several other natural fiber‐epoxy composites. Cole–Cole plots indicated improved resin‐fiber adhesion for composites containing 0.75‐ and 1‐h treated husk fibers. Phase angle data confirmed enhanced energy dissipation and viscoelastic behavior. Thermo‐mechanical stability improved, with the 0.75‐h treated fiber composite showing the lowest total mass loss (0.4%). Overall, alkali‐treated Borassus husk fiber composites exhibited superior mechanical stiffness, damping capacity, and thermal stability, making them ideal for aerospace and automotive applications requiring strength, impact resistance, and sustainability. It will also contribute to achieving the “net‐zero” target established in the 2015 Paris Agreement

Palmyra Palm Shell (Borassus flabellifer) Properties Part 1: Insights Into Its Physical and Chemical Properties

Bio-based materials are gaining importance in engineering due to their availability, recyclability, and eco-friendliness. Among them, Borassus flabellifer (Palmyra palm) fruit shell (husk) is an underutilized biofiber in Bangladesh, currently limited to disposal or waste-to-energy applications despite its potential for high-value uses. This study explores the physical, chemical, and microstructural properties of untreated Borassus flabellifer husk to evaluate its suitability as a sustainable material for engineering applications. The physical properties, including density, water absorption, moisture regain, and porosity, were assessed according to BS EN ISO 1183-1:2019, ASTM D750, ASTM D2654-22, and ISO 2738 standards. The husk was found to be significantly lighter than its fine as well as coarse fibers and conventional natural fibers like jute, flax, and sisal, making it ideal for lightweight engineering designs. FTIR analysis (qualitatively) revealed the presence of cellulose, hemicellulose, and lignin, which contribute to its mechanical strength, water absorption, and thermal insulation properties, respectively. SEM analysis further demonstrated a cross-linked, porous, and tubular fiber structure, enhancing its thermal and sound insulation features. The findings suggest untreated Borassus flabellifer husk can be a promising alternative for applications requiring lightweight, thermally, and acoustically insulating materials. While its moisture and water resistance outperform some biofibers, chemical treatments could enhance these properties further. To maximize its potential, efficient collection and supply chain systems are essential for industrial-scale production. Harnessing this abundant resource could support sustainable development while encouraging the cultivation and preservation of Borassus flabellifer trees

An investigation into differences in general intelligence and coaches' subjective assessment of players' decision-making skills across different playing positions in EPPP association football academies

With developments in tactical complexity in association football (soccer) general intelligence and decision-making are becoming increasingly important attributes for players at all levels. However, an absence of evidence regarding general intelligence and decision-making across different positions within English Academy soccer indicates that it is unknown how specific intelligence in soccer needs to be for successful performance. This study aimed to 1) examine differences in general intelligence scores between different playing positions, 2) investigate differences in coach assessed decision-making ability between different playing positions and 3) assess differences between general intelligence test score ranks and decision-making ranks awarded by coaches to each player per position. One hundred and one participants, aged 16–18 years were recruited from eight clubs in the English Football League. Participants completed an established psychometric test of general intelligence and the lead development phase coach at each club ranked players' decision-making ability. There were 99 outfield players who participated: 37 defenders, 34 midfielders and 28 attackers. No difference was found in general intelligence scores between playing positions. However, a significant difference was found in decision-making ranks, with coaches determining attacker's decision-making to be lower than midfielders and defenders. Likewise , no difference was found between general intelligence and decision-making ranks for either defenders or midfielders, but a difference was observed between attackers' general intelligence and decision-making ranks. In conclusion, attacker's game intelligence appears to be underestimated by coaches. Consequently, utilisation of a psychometric test of general intelligence could enhance identification of talented players in Academy soccer

AI Agents: A Comprehensive Review of Evolution, Architectures, Applications, and Future Directions

Technology is rapidly evolving, with the use and adoption of AI agents on the rise. This paper presents a critical review of the evolution, architectures, applications, and future directions of AI agents. This review brings to fore the fact that currently, Ai agents had become highly sophisticated, with an ability to execute tasks that are complex across several fields of such as business, health and medicine and cybersecurity. However, despite these benefits, there still exist concerns such as limited reasoning, inefficient context management, and idea generalisation. Other challenges of AI agents include algorithmic bias and privacy violations. To address the identified challenges, this paper suggests that for future works on AI agents should prioritise coming up with architectures with advanced reasoning, efficient and good memory usage, AI-human collaboration, introduction of standardised frameworks, and applications of AI in scientific discovery. The contribution of this work to the existing body of academic discussion is a comprehensive assessment of AI agents, showing the capabilities, challenges, and the areas for future development. Although AI agents promise great advantages, the utilisation of these goods that it promises depends on clear understanding to the challenges, limitations and the inherent ethical and security risks and providing clear and timely solutions through continued interdisciplinary research and engagements