1,721,000 research outputs found
Lifecyle Design and Effectiveness Evaluation for Simulated Translation Agencies
Full text linkCurrent demands from technology-based translation industry and market require adequate educational offerings to be provided at Master's Level Degree. Therefore, novel and more engaging strategies for complementing traditional theoretical lessons and laboratory sessions on computer-assisted translation are needed to improve students' skills and technical acquaintance, as suggested by the European Master's in Translation Competence Framework. The Simulated Translation Agency (STA) holistic approach promises to be a key enabler capable of motivating students to manage a fictional company according to a professional translation workflow. In this paper, a methodology based on Business Process Modelling (BPM) for designing cloud-enabled STAs grounded on competence frameworks and professional standards is proposed, along with a set of metrics targeting student self-assessment and agency productivity. The "STARS" agency, designed and deployed according to the proposed methodology in an Italian university, is described in detail as a test case. Achieved results demonstrate the effectiveness of this approach as well as the significant engagement of participants
Incorporating Collaborative and Active Learning Strategies in the Design and Deployment of a Master Course on Computer-Assisted Scientific Translation
Full text linkThis research aims to address the current gaps in computer-assisted translation (CAT) courses offered in bachelor’s and master’s programmes in scientific and technical translation (STT). A multi-framework course design methodology is proposed to support CAT teachers from the computer engineering field, improve student engagement, and promote computer-supported education, together with a balanced coverage of the most relevant topics in the CAT domain. STT is currently in high demand in many fields, requiring translators with sector-specific language skills and considerable computer literacy in order to manage translation projects with complex structures, and format heterogeneity. However, many STT curricula often lag behind current market demands, focusing primarily on language and translation theory, with less emphasis on CAT technologies and tools. Moreover, the lack of shared course design guidelines hinders the introduction of innovative teaching approaches based on collaborative learning. A novel multi-framework CAT course design methodology, named CATDeM, is proposed, based on the integration between an official European translation competence framework, real-life-mimicking laboratorial activities, and computer-supported collaborative learning, enriched with discussion case studies and role-playing experiences. A real-life case study is examined to illustrate and evaluate the implementation of CATDeM in two consecutive editions (2020/2021 and 2021/2022) of a one-semester compulsory CAT course in a M.A. degree in STT at the University of Salento (Italy). Students’ perceptions of translation technology and role-plays, as well as their attitudes towards the proposed CAT course are evaluated through a post-grading self-assessment questionnaire. Achieved results indicated successful student engagement and self-assessed improvement in translation, technical, and interpersonal skills. The importance given by students to role-playing experiences mimicking professional scenarios was also highlighted, paving the way for CATDeM to be adopted in similar contexts
The Immersive Workbench for Engineering Educators: (Re)Thinking Collaborative and Distance Learning Platforms as Technological Enablers
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Adopting machine translation in the healthcare sector: A methodological multi-criteria review
No full textBackground: The recent advances in machine translation (MT) offer an appealing and low-cost solution to overcome language barriers in multiple contexts (e.g., travelling, cultural interaction, digital content localisation). However, highly-technical domains typically exhibiting as long, complex, and specialised texts as the healthcare sector, pose multiple challenges to the effective and risk-safe use of MT. Methods: To examine how MT nowadays assists written/verbal health communication and because of the existing considerable heterogeneity in technological enablers, language pairs and user groups, training approaches, evaluation processes, and users” requirements, we propose in this paper a methodological multi-criteria literature review based on current guidelines in computer science research and grounded on a customised configuration of the PRISMA methodology, normally used to perform meta-analyses on clinical trials. The review focuses on language-to-language medical MT, covers the time period January 2015–February 2023, and only refers to articles written in English that are accessible via four scientific online digital libraries. Articles are ranked according to a meta-evaluation scoring method for MT scientific credibility along with a scoring for assessing the scope of MT in healthcare. Finally, a guideline to properly design a study about MT in healthcare is also proposed. Results: The review included a final set of 58 articles from journals (n=30) and conference proceedings (n=28), considering 48 different language combinations. We identified a predominance of English-to-Spanish (n=19) and English-to-Chinese (n=16) implementations, mainly tailored to medical staff only (n=14) or along with patients (n=12). Included papers addressed clinical communication (n=21) and health education (n=37). Unidirectional real-time bilingual MT (n=24) was the most frequent configuration. MT implementations were dominated by Google Translate (n=22) often used as baseline, OpenNMT (n=12), or Moses (n=11). Training and evaluation approaches varied considerably, while deployment and pre-/post-editing were rarely described with an adequate level of detail. Conclusion: Even if a significant number of articles reported that the proposed MT solutions were effective when translating (bio)medical texts, only a subset of them complied with rigorous translation quality assessment criteria (e.g., use of automatic metrics better related to human ranking than BLEU or statistical significance testing). Nevertheless, MT can be a valid support/supplement in health communication but to cope with issues in fluency, accuracy, unnatural translations, domain-adequacy, and potential safety risks (for highly-sensitive documents), appropriate MT training is essential, along with in-domain human post-editing. The presence of in-domain training text corpora has also proven to be beneficial. Finally, guidelines about how to design studies on MT in healthcare are also proposed to engage more researchers in this field
Online lexical resources for translators: where do we stand? A (possibly meaningful) case-study
No full textBy means of a case-study of word ‘jab’ in its medical sense, this work aims to assess the effectiveness of a range of online lexical resources in providing word meanings. These include: monolingual and bilingual dictionaries; corpora; and machine translation services
Towards an Italian Energy Data Space
Full text linkThe efficient use and the sustainable production of energy are some of the main challenges to face the ever increasing request for energy and the need to limit the damages to the Earth. Smart energy grids, pervasive computing and communication technologies have enabled the stakeholders in the energy industry to collect large amounts of useful and highly granular energy data. They are generated in large volumes and in a variety of different formats, depending on their originating systems and prospected purposes. Moreover, the data type can be structured and unstructured, in open or proprietary formats. This work focuses on harnessing the power of Big Data Management to propose a first model of an Italian Energy Data Lake: the goal is to create a repository of national energy data that respects the FAIRness' key principles [1], aimed at providing a decision support system and the availability of FAIR data for open science. Starting from data of two thematic areas that are part of the nine common European Data Spaces identified in the European Data Strategy[2], namely the Green Deal data space and the Energy data space, an open and extensible platform to enable secure, resilient acquisition and sharing of information will be presented, for enabling the Green Deal priority actions on issues such as climate change, circular economy, pollution, biodiversity, and deforestation
A User-Centered Approach to Create Realistic Datasets for AI. Case Study: Creditworthiness in the Banking Sector
No full textA Versatile Context-Aware Pervasive Monitoring System: validation and characterization in the health-care domain
No full textA cloud-based approach to dynamically manage service contracts for local public transportation
No full textPublic contracts regulate how public services are managed by the stakeholders. However, the current technological trend is creating a significant bias between the pace at which service data are produced and that at which contracts change. This increased availability of service data can be exploited in public procurement processes by fostering novel approaches to manage contracts, making them more dynamic and improving the Quality of Service (QoS) delivered to customers. In this paper, a cloud-based approach for assessing the QoS in Local Transportation Services (LTSs) in Apulia Region (Southern Italy) is proposed. Service Level Agreements (SLAs) between providers and the Regional Authority, as well as the minimal guaranteed QoS levels between providers and passengers, are modelled as contracts enacted via a cloud-based system, which gathers data from sensors and passengers. In this way, changes in contract conditions for improving the perceived and delivered QoS can be fastened and facilitated based on data. In order to validate the pilot case, a set of quality indicators and service levels grounded in European and Italian regulatory frameworks has been considered
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