1,721,021 research outputs found
HUMOSEXUALLY SPEAKING: Laughter and the Intersections of Gender
No full textLo humour può essere un’attività molto rischiosa, in particolar modo quando denigra le minoranze. Le persone ridono per le più disparate banalità, spesso senza tener conto che qualcuno, attraverso quelle stesse banalità, possa essere schernito al punto di divenire una vera e propria vittima sociale. Immagini stereotipate nascono da atteggiamenti negativi nei confronti di alcuni gruppi sociali e creano un pregiudizio di lunga durata. L’immagine distorta che passa attraverso l'umorismo ha la funzione di ingabbiare le persone LGBTI in rappresentazioni negative, che spesso includono riferimenti alla malattia e alla morte, oppure ritraggono tali gruppi come maniaci sessuali o pervertiti. Attraverso l’umorismo, queste caratteristiche si innestano nelle più comuni pratiche sociali, che rappresentano così l’origine di pregiudizi basati in genere sul rifiuto del gruppo preso a bersaglio. La ripetizione della stessa rappresentazione negativa può infine portare alla formazione di discorsi sedimentati in diversi contesti sociali: in questo modo tali rappresentazioni ideologiche stereotipate diventano parte di un discorso significante comune, e non più immediatamente percepibili come ideologie negative o di esclusione.
Analizzando la funzione sociale dello humour in comunità di persone lesbiche, gay, bisessuali, transgender e intersessuali in contesti postcoloniali, ci preme sottolineare il modo in cui l'umorismo ha il potere di rafforzare e reinterpretare costantemente l'esclusione sociale, culturale e giuridica di alcuni membri della società.
L'omosessualità nel discorso umoristico è un argomento molto serio. Tuttavia, non si è ancora affrontata un'indagine sistematica sul rapporto tra umorismo e tematiche e/o persone LGBTI; in particolare, non vi è alcuna ricerca coerente sulla questione in contesti postcoloniali.
La nostra proposta invita contributi originali su riflessioni teoriche, così come l'esplorazione analitica del linguaggio umoristico, delle rappresentazioni di comici, oltre che di blog, film, serie tv ed altri prodotti scritti e/o audiovisivi pertinenti alle tematiche individuate e generate in paesi di lingua inglese.Humour can be a very dangerous activity, especially if laughter works at downplaying minority groups. People will generally laugh at anything despite the fact that somebody – or some specific groups – may be insulted by being the butt of a joke. The biased image which tends to pass through humour construes LGBTI people within negative representations, encompassing illness and death, but also depicting them as sex maniacs or perverts. Through humour, these features are often taken for granted by the whole of society, constituting the origin of prejudices which are commonly based upon the rejection of the targeted group. The repetition of the very same biased representation can lead to the formation of accepted discourses in various societies bringing jaundiced ideological representations to the status of semiosis, therefore no longer visible as negative or exclusionary ideologies.
Focusing on the social function of humour in lesbian, gay, bisexual, transgender and intersex communities in postcolonial settings, we wish to posit that humour also has the power to constantly strengthen and re-interpret the social, cultural and legal exclusion of some fully-fledged members of society.
Homosexuality in humorous discourses is a very hot topic. However, there has been very little systematic investigation into the relationship between humour and LGBTI people, and in particular, there is no consistent research about the issue in postcolonial contexts
Small models, big impact: A review on the power of lightweight Federated Learning
No full textFederated Learning (FL) enhances Artificial Intelligence (AI) applications by enabling individual devices to collaboratively learn shared models without uploading local data with third parties, thereby preserving privacy. However, implementing FL in real-world scenarios presents numerous challenges, especially with IoT devices with limited memory, diverse communication conditions, and varying computational capabilities. The research community is turning to lightweight FL, the new solutions that optimize FL training, inference, and deployment to work efficiently on IoT devices. This paper reviews lightweight FL, systematically organizing and summarizing the related techniques based on its workflow. Finally, we indicate potential problems in this area and suggest future directions to provide valuable insights into the field
Queering Laughter? It was just a joke!
Full text linkHumosexually Speaking - Laughter and the Intersections of Gender investigates the social function of humour produced in, against and about gender variant communities of speakers, in both verbal and multimodal forms. The editors’ leading idea was to ignite an academic discussion on the several and often hidden ways through which humour succeeds in constantly strengthening and/or re-interpreting, but also dismantling, the social dimension of language. One of the possible results of such a political and social act is the fostering of the cultural exclusion of some gendered, or rather de-generated – as some discriminated groups tend to be commonly alleged to be – minority communities. Additionally, since humour may also work to signify the recurring upsetting of pre-established social beliefs through the systematic threatening of the familiar, the normative, and what is universally deemed as socially acceptable or “normal”, debates on any form of humorous self-representation of gendered identities were also vivid in the editors’ minds. In particular, it seemed fascinating to encouraging a discussion on the way LGBTI communities, just like other marginalised groups, would employ humour to support and reinforce their own in-group sense of community, by mocking typically stereotyped representations of gender variant people who laugh at and with themselves. Although LGBTI humour is still a very hot topic in our western world, one reason for the lack of a real academic confrontation on its social and political mechanisms resides in the very difficult challenge of defining it. Specifically, despite a convincing semantic linguistic theory of humour introduced by Raskin (1985) and later developed by Attardo (1994; 2001), the cultural mechanisms underlying some jokes laughing about human relationships by queering the scene, for instance, are still an unexplored topi
The Lexicogrammatical Company that James Joyce Keeps
No full textThis chapter analyses how James Joyce has been represented in the British press by investigating a large corpus of British newspapers from 1993 and 1995, using the tools of corpus-assisted discourse analysis (for example, see Morley and Bayley eds 2009) and accordingly its focus goes beyond the nine-word window typical of a great deal of corpus linguistics. The chapter first describes the corpus we used for the study, the procedures used to narrow down the data, and the quantitative data resulting from a query for ‘Joyce’. Secondly, it offers an analysis of the semantic sets that are associated with mentions of his name, which means searching through the concordances not for collocates but for co-occurrences of items with similar meanings or with similar grammatical configurations. Finally, it probes what is at stake in the use of a word that does not refer to the author himself, but rather is applied primarily to objects represented as similar to him – Joycea
GRAPHITE — Generative Reasoning and Analysis for Predictive Handling in Traffic Efficiency
No full textTraffic forecasting is a crucial aspect of modern Intelligent Transportation Systems (ITS) and the Internet of Vehicles (IoV), playing a vital role in improving the safety and efficiency of daily transportation activities. Despite the valuable contributions of traditional machine learning (ML) models and advanced deep learning (DL) techniques, there persist challenges in capturing the intricate spatial and temporal dependencies inherent in traffic flow. In response to these challenges, we present GRAPHITE, an innovative framework that combines Graph Neural Networks (GNNs) and Generative Adversarial Networks (GANs) to leverage generative reasoning for efficient traffic management. Our model seamlessly integrates historical traffic volume data collected by road sensors with local spatial information encoded through knowledge graphs (KGs) associated with each sensor. These KGs offer a structured representation of relationships between traffic sensors and points of interest (POIs) in their neighborhood, thereby enhancing the comprehension of the urban context and leading to more accurate traffic predictions. Extensive experiments conducted on diverse datasets underscore the efficacy of GRAPHITE. Notably, we achieved a maximum decrease in RMSE of 31.05% compared to GAN-GRU and a maximum increase in R2 of 8.15% compared to GAN-RNN, positioning GRAPHITE as a standout solution among the current state-of-the-art approaches. Our code is available at: https://github.com/MODAL-UNINA/GRAPHITE
SHELOB-FFL: addressing Systems HEterogeneity with LOcally Backpropagated Forward-Forward Learning
No full textFederated Learning (FL) is a method for training Machine Learning (ML) models across various clients while maintaining data privacy. Addressing the challenge of client resource diversity, this paper presents a novel approach combining the Forward-Forward (FF) algorithm with Back Propagation (BP). This integration forms a blockwise network structure that achieves robust convergence without the chain rule, dividing the model into subnetworks for efficient training. The strategy allows dynamic allocation of network segments to clients based on their computational resources, enabling independent optimization of subnetworks, thus preventing delays and memory issues. Experiments in IID and non-IID settings across datasets assess the methodology's viability, focusing on the impact of data and label distribution on convergence. The study also examines weight aggregation and regularization techniques like FedAvg and FedProx, adapting them to understand their effect on this FL approach. Source code available at: https://github.com/MODALUNINA/SHELOB_FF
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Interpreters’ perception of linguistic and non linguistic factors affecting quality: a survey through the World Wide Web
No full textThis paper will present and discuss the results of an empirical study on perception of quality in interpretation carried out on a sample of 286 interpreters across five continents. Since the 1980’s the field of Interpreting Studies has been witnessing an ever growing interest in the issue of quality in interpretation both in academia and in professional
circles, but research undertaken so far is surprisingly lacking in methodological rigour. This survey is an attempt to revise previous studies on interpreters’ perception of quality through the implementation of new Information Technology which allowed us to administer a traditional research tool such as a questionnaire, in a highly innovative way; i.e., through the World Wide Web. Using multidimensional scaling, a perceptual map based upon the results of the manner in which interpreters ranked a list of linguistic and nonlinguistic criteria according to their perception of importance in the interpretative process,was devised
Food and translation, translation and food. Introduction
Full text linkFood, the cornerstone of life, lies at the heart of our cultural identity. Vital for our
health and well-being, our awareness of its economic, cultural and social significance -
how the language of food and related practices travel across languages and cultures
cannot be disregarded. Despite a rapidly expanding market for translation of food
related texts: cookery books and TV programmes, magazines and food labels, to name
just a few, and despite fast-pace evolving eating habits and phenomena, the relationship
between food, culture and translation remains under-researched. By bringing these
issues to light, this special issue aims to be a truly interdisciplinary reference work that
brings together expert scholars writing on food related topics from a translational and
intercultural perspective
Ablation Studies in Activation Maps for Explainable Semantic Segmentation in Industry 4.0
No full textIn recent years, much attention has been given to various eXplainable Artificial Intelligence (XAI) and interpretability methods. Their extension to dense prediction tasks, however, has been underexplored. Gradient-based saliency maps, highlighting feature importance in terms of input pixels, have been frequently used as fast and simple visual explanation techniques. Nonetheless, they face several problems, and the exploration of different types of attribution methods is warranted. In this paper, we investigate gradient-free semantic segmentation explanations that are based on ablating activation maps. We explore their potential for industrial applications, specifically for fruit pitting machines. We also extend the application of Ablation-CAM, a gradient-free ablation-based interpretability technique, to semantic segmentation. Finally, we discuss the sensitivity of activation maps to partial occlusions of either the foreground or the background class regions
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