9,890 research outputs found

    Anuário científico da Escola Superior de Tecnologia da Saúde de Lisboa - 2021

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    É com grande prazer que apresentamos a mais recente edição (a 11.ª) do Anuário Científico da Escola Superior de Tecnologia da Saúde de Lisboa. Como instituição de ensino superior, temos o compromisso de promover e incentivar a pesquisa científica em todas as áreas do conhecimento que contemplam a nossa missão. Esta publicação tem como objetivo divulgar toda a produção científica desenvolvida pelos Professores, Investigadores, Estudantes e Pessoal não Docente da ESTeSL durante 2021. Este Anuário é, assim, o reflexo do trabalho árduo e dedicado da nossa comunidade, que se empenhou na produção de conteúdo científico de elevada qualidade e partilhada com a Sociedade na forma de livros, capítulos de livros, artigos publicados em revistas nacionais e internacionais, resumos de comunicações orais e pósteres, bem como resultado dos trabalhos de 1º e 2º ciclo. Com isto, o conteúdo desta publicação abrange uma ampla variedade de tópicos, desde temas mais fundamentais até estudos de aplicação prática em contextos específicos de Saúde, refletindo desta forma a pluralidade e diversidade de áreas que definem, e tornam única, a ESTeSL. Acreditamos que a investigação e pesquisa científica é um eixo fundamental para o desenvolvimento da sociedade e é por isso que incentivamos os nossos estudantes a envolverem-se em atividades de pesquisa e prática baseada na evidência desde o início dos seus estudos na ESTeSL. Esta publicação é um exemplo do sucesso desses esforços, sendo a maior de sempre, o que faz com que estejamos muito orgulhosos em partilhar os resultados e descobertas dos nossos investigadores com a comunidade científica e o público em geral. Esperamos que este Anuário inspire e motive outros estudantes, profissionais de saúde, professores e outros colaboradores a continuarem a explorar novas ideias e contribuir para o avanço da ciência e da tecnologia no corpo de conhecimento próprio das áreas que compõe a ESTeSL. Agradecemos a todos os envolvidos na produção deste anuário e desejamos uma leitura inspiradora e agradável.info:eu-repo/semantics/publishedVersio

    Deep Transfer Learning Applications in Intrusion Detection Systems: A Comprehensive Review

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    Globally, the external Internet is increasingly being connected to the contemporary industrial control system. As a result, there is an immediate need to protect the network from several threats. The key infrastructure of industrial activity may be protected from harm by using an intrusion detection system (IDS), a preventive measure mechanism, to recognize new kinds of dangerous threats and hostile activities. The most recent artificial intelligence (AI) techniques used to create IDS in many kinds of industrial control networks are examined in this study, with a particular emphasis on IDS-based deep transfer learning (DTL). This latter can be seen as a type of information fusion that merge, and/or adapt knowledge from multiple domains to enhance the performance of the target task, particularly when the labeled data in the target domain is scarce. Publications issued after 2015 were taken into account. These selected publications were divided into three categories: DTL-only and IDS-only are involved in the introduction and background, and DTL-based IDS papers are involved in the core papers of this review. Researchers will be able to have a better grasp of the current state of DTL approaches used in IDS in many different types of networks by reading this review paper. Other useful information, such as the datasets used, the sort of DTL employed, the pre-trained network, IDS techniques, the evaluation metrics including accuracy/F-score and false alarm rate (FAR), and the improvement gained, were also covered. The algorithms, and methods used in several studies, or illustrate deeply and clearly the principle in any DTL-based IDS subcategory are presented to the reader

    Exploring Employees\u27 Perceptions of the Learning Organization and Their Learning Experiences in a Georgia State Government Agency – A Concurrent Mixed Methods Study

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    This concurrent Mixed Methods (MM) research study explored employee learning perceptions and experiences in a state of Georgia government agency. The study used the Dimension of the Learning Organization Questionnaire (DLOQ) to examine employee perceptions of a learning organization across management levels and tenure. It also used semi-structured phenomenological interviews to examine learning experiences. The two questions that framed the study were: (1) How do employees navigate learning individually, in teams, and organizationally? (2) How do employee perceptions of the learning organization compare based on tenure and management level? The concurrent mixed methods design allowed for comparison of findings from the questionnaire and the interviews. Participants were simultaneously recruited from the same state of Georgia government agency to complete the questionnaire and interview voluntarily. Three hundred and thirty-eight (338) employees responded to the questionnaire, the quantitative (QUAN) strand. Five (5) employees participated in the interviews, the qualitative (QUAL) strand. The interview data was analyzed using a hybrid/eclectic methodology of coding, theming, and analytic memos. The questionnaire data was analyzed using descriptive and non-parametric statistical tests. The findings of the study suggest that leadership influences learning critically. For this organization to continue learning and growing, it must focus on the leaderships’ impact on its employees\u27 learning in the work environment. Additionally, significant differences in employee perceptions of the learning organization were observed. These differences were between employees with 6 to 10 years and those with 16 to 20 years of tenure on Inquiry/Dialogue (Dimension 2), Organization Environment Connection (Dimension 6), and Individual Level learning (Level 1). While the findings present possible explanations for the differing perceptions, future research should examine this further

    Examining the Impact of Personal Social Media Use at Work on Workplace Outcomes

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    A noticable shift is underway in today’s multi-generational workforce. As younger employees propel digital workforce transformation and embrace technology adoption in the workplace, organisations need to show they are forward-thinking in their digital transformation strategies, and the emergent integration of social media in organisations is reshaping internal communication strategies, in a bid to improve corporate reputations and foster employee engagement. However, the impact of personal social media use on psychological and behavioural workplace outcomes is still debatebale with contrasting results in the literature identifying both positive and negative effects on workplace outcomes among organisational employees. This study seeks to examine this debate through the lens of social capital theory and study personal social media use at work using distinct variables of social use, cognitive use, and hedonic use. A quantitative analysis of data from 419 organisational employees in Jordan using SEM-PLS reveals that personal social media use at work is a double-edged sword as its impact differs by usage types. First, the social use of personal social media at work reduces job burnout, turnover intention, presenteeism, and absenteeism; it also increases job involvement and organisational citizen behaviour. Second, the cognitive use of personal social media at work increases job involvement, organisational citizen behaviour, employee adaptability, and decreases presenteeism and absenteeism; it also increases job burnout and turnover intention. Finally, the hedonic use of personal social media at work carries only negative effects by increasing job burnout and turnover intention. This study contributes to managerial understanding by showing the impact of different types of personal social media usage and recommends that organisations not limit employee access to personal social media within work time, but rather focus on raising awareness of the negative effects of excessive usage on employee well-being and encourage low to moderate use of personal social media at work and other personal and work-related online interaction associated with positive workplace outcomes. It also clarifies the need for further research in regions such as the Middle East with distinct cultural and socio-economic contexts

    Freelance subtitlers in a subtitle production network in the OTT industry in Thailand: a longitudinal study

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    The present study sets out to investigate a subtitle production network in the over-the-top (OTT) industry in Thailand through the perspective of freelance subtitlers. A qualitative longitudinal research design was adopted to gain insights into (1) the way the work practices of freelance subtitlers are influenced by both human and non-human actors in the network, (2) the evolution of the network, and (3) how the freelance subtitlers’ perception of quality is influenced by changes occurring in the network. Eleven subtitlers were interviewed every six months over a period of two years, contributing to over 60 hours of interview data. The data analysis was informed by selected concepts from Actor-Network Theory (ANT) (Law 1992, 2009; Latour 1996, 2005; Mol 2010), and complemented by the three-dimensional quality model proposed by Abdallah (2016, 2017). Reflexive thematic analysis (Braun and Clarke 2019a, 2020b) was used to generate themes and sub-themes which address the research questions and tell compelling stories about the actor-network. It was found that from July 2017 to September 2019, the subtitle production network, which was sustained by complex interrelationships between actors, underwent a number of changes. The changes affected the work practices of freelance subtitlers in a more negative than positive way, demonstrating their precarious position in an industry that has widely adopted the vendor model (Moorkens 2017). Moreover, as perceived by the research participants, under increasingly undesirable working conditions, it became more challenging to maintain a quality process and to produce quality subtitles. Finally, translation technology and tools, including machine translation, were found to be key non-human actors that catalyse the changes in the network under study

    AIUCD 2022 - Proceedings

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    L’undicesima edizione del Convegno Nazionale dell’AIUCD-Associazione di Informatica Umanistica ha per titolo Culture digitali. Intersezioni: filosofia, arti, media. Nel titolo è presente, in maniera esplicita, la richiesta di una riflessione, metodologica e teorica, sull’interrelazione tra tecnologie digitali, scienze dell’informazione, discipline filosofiche, mondo delle arti e cultural studies

    Graphical scaffolding for the learning of data wrangling APIs

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    In order for students across the sciences to avail themselves of modern data streams, they must first know how to wrangle data: how to reshape ill-organised, tabular data into another format, and how to do this programmatically, in languages such as Python and R. Despite the cross-departmental demand and the ubiquity of data wrangling in analytical workflows, the research on how to optimise the instruction of it has been minimal. Although data wrangling as a programming domain presents distinctive challenges - characterised by on-the-fly syntax lookup and code example integration - it also presents opportunities. One such opportunity is how tabular data structures are easily visualised. To leverage the inherent visualisability of data wrangling, this dissertation evaluates three types of graphics that could be employed as scaffolding for novices: subgoal graphics, thumbnail graphics, and parameter graphics. Using a specially built e-learning platform, this dissertation documents a multi-institutional, randomised, and controlled experiment that investigates the pedagogical effects of these. Our results indicate that the graphics are well-received, that subgoal graphics boost the completion rate, and that thumbnail graphics improve navigability within a command menu. We also obtained several non-significant results, and indications that parameter graphics are counter-productive. We will discuss these findings in the context of general scaffolding dilemmas, and how they fit into a wider research programme on data wrangling instruction
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