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Gendered Islamophobia: the challenges facing Muslim women today and the ways in which those challenges can be best addressed
No full textDisaster identification scheme based on federated learning and Cognitive Internet of Vehicles
No full textThe rate of disaster occurrences has been increasing over the last decade due to the alarming effects of global warming. A major challenge with such disasters is identifying their nature before substantial loss of lives and property occurs. Existing systems often fail to determine the type of disaster until significant damage has been done. This research proposes a novel scheme to identify disasters as they occur, leveraging Federated Learning (FL) and Cognitive Internet of Vehicles (CIoV) since vehicles are a common presence in disaster scenarios. The proposed scheme utilizes various machine learning (ML) and deep learning algorithms to predict disaster types in real-time. Additionally, it introduces a custom federated averaging algorithm to maintain result privacy. The research evaluated the scheme’s performance using a data set of recorded disasters from various countries, training different algorithms to determine optimal results. The results indicate that the proposed scheme can achieve a 90% accuracy in disaster-type identification using deep learning and random forest algorithms
Geography Fieldwork: Effective Learning or a Good Day Out? Comparing the Impacts of Fieldwork and Classroom Learning in the Cognitive and Affective Domains: A Quasi-Experiment and Mixed Methods Approach
No full textContemporary Issues in Music Therapy Training: A resource for trainees, trainers and practitioners
No full textHow and When Ethics-oriented Human Resource Management Systems Promote Organizational Citizenship Behavior: The Moderated Mediation of Work-Family Balance and Moral Attentiveness
No full textEmployees’ organizational citizenship behavior (OCB) is an important determinant of organizational effectiveness; hence, scholars and practitioners are particularly interested in the factors, mechanisms, and conditions that promote such behaviors. Guided by the ability–motivation–opportunity framework, we draw on the social cognitive theory of moral thought and action to conceptualize a model that delineates the role of ethics-oriented human resource management (HRM) systems in promoting OCBs through the mediating role of employees’ moral attentiveness. We also refer to the job demands–resources theory to describe the moderating role of work-family balance in the indirect relationship between HRM systems and OCBs. The findings of an experiment involving 157 working adults (Study 1) and a three-wave field survey of 328 employees (Study 2) converge to support the hypothesized direct and indirect (via moral attentiveness) relationships between ethics-oriented HRM systems and OCBs as well as the first-stage moderating role of work-family balance
Disco as Open Image: Internet Sightings, Cryptic Denotations, and Disco Dancing Girls
No full textThis chapter explores a riddle: what can we learn from digital images that circulate the internet under a “disco” guise, even when the stylistic and cultural traits of disco are hardly present? Particularly of interest here are several images named as “disco dancing girls” that arguably operate on the register of [disco] “sightings,” activating layered mechanisms of apophenia and stereotyping. When considered as cryptic sightings, these online “disco girls” reveal something important about the images they occupy, as well as about “disco” as a present-day signifier. Firstly, by animating historical girlhood references, these images offer us revelations about internet’s girl cultures today and historically. The duality of objectification and agency, upon a closer look, is found equally in the historic school discos and contemporary “soft girl” bedroom-disco social media posts. Secondly, the disco naming reframes these images as they cluster with other “poor images.” Finally, we learn something significant about the “disco” label as it produces “open images” or opens out the unlikely disco representations toward new realities, narratives, and fantasies
Transforming Disability Into Ability: An Explainable Vision-to-Voice Image Captioning Framework Using Transformer Models and Edge Computing
No full textBarriers to African parental involvement within the UK education system
No full textEven though students from African backgrounds have above-average education achievements in the UK, some students still struggle to integrate into the school systems. Parental involvement has been reported to have a significant influence on pupil achievement. Thus, this research aimed to identify parental involvement barriers experienced by African parents. The researcher conducted five focus group interviews with 32 black African parents living in the UK. The focus groups were both on Zoom and face-to-face. The participants immigrated to the UK from different parts of Africa as adults or in their late teenage years. The Africa ethos of collaboration and dialogue were utilised to help participants freely discuss their experiences. The approach was formed from an empowerment perspective, aiming to break the top-down barriers that hinder African parental involvement. Thematic analysis was used to reveal emerging themes. This study findings indicated cultural and structural factors that need addressing, such as prejudice from teachers, poor communication systems between schools and parents about the curriculum, and expectations for parents’ involvement. In addition, many parents voiced a lack of understanding of the school system, hindering their involvement. The issues identified in the study need to be acknowledged and addressed collaboratively by key players to enhance the best outcomes for children from black African families
Gospel, Liberation and Pluralism in Latin America
No full text© 2024, [SAGE Publications Limited]. This is an author produced version of a paper published in Transformation: An International Journal of Holistic Mission Studies uploaded in accordance with the publisher’s self- archiving policy. The final published version (version of record) is available online at the link. Some minor differences between this version and the final published version may remain. We suggest you refer to the final published version should you wish to cite from it. Seeing the world through the eyes of the marginalised has been a consistent theme in modern Latin American theology. When Latin American Liberation Theology first emerged, evangelical theologian René Padilla expressed a shared concern over the problem of poverty. But he also warned that certain elements therein clashed with evangelical hermeneutics. Consequently, he called for a circular approach that would maintain a tension between the crisis of the moment and the authority of biblical revelation. In the 21st century, liberation discourse has expanded into postcolonial critique on indigenous culture and identity, including a stream known as Liberation Pluralism. Evangelicals share many of the same concerns. But as they engage with the discourse, there is an ongoing need to heed Padilla’s warning. This article argues that evangelicals today can engage in postcolonial and liberation discourses, but that this should be carried out with that same circular hermeneutic which Padilla first proposed
Knowledge-Grounded Attention-Based Neural Machine Translation Model
No full textNeural machine translation (NMT) model processes sentences in isolation and ignores additional contextual or side information beyond sentences. The input text alone often provides limited knowledge to generate contextually correct and meaningful translation. Relying solely on the input text could yield translations that lack accuracy. Side information related to either source or target side is helpful in the context of NMT. In this study, we empirically show that training an NMT model with target-side additional information used as knowledge can significantly improve the translation quality. The acquired knowledge is leveraged in the encoder-/decoder-based model utilizing multiencoder framework. The additional encoder converts knowledge into dense semantic representation called attention. These attentions from the input sentence and additional knowledge are then combined into a unified attention. The decoder generates the translation by conditioning on both the input text and acquired knowledge. Evaluation of translation from Urdu to English with a low-resource setting yields promising results in terms of both perplexity reduction and improved BLEU scores. The proposed models in the respective group outperform in LSTM and GRU with attention mechanism by +3.1 and +2.9 BLEU score, respectively. Extensive analysis confirms our claim that the translations influenced by additional information may occasionally contain rare low-frequency words and faithful translation. Experimental results on a different language pair DE-EN demonstrate that our suggested method is more efficient and general