La mémoire de projet : véhicule d’intégration de l’ergonomie et de la SST à la conception ?

Pour les ergonomes et les préventionnistes, faire évoluer la conduite de projet afin de pouvoir influencer efficacement la conception des situations de travail constitue un enjeu majeur. Cet article traite d’un levier d’amélioration continue des projets qu’ils pourraient exploiter avantageusement pour soutenir leurs efforts : la mémoire de projet. L’article résume d’abord ce qui est dit de cet outil dans la littérature issue des domaines de la gestion de projet et des organisations. Puis, il propose aux intervenants en ergonomie et en SST des leçons à tirer de la mémoire de projet pour soutenir leurs efforts d’intégration à la conception : infiltrer les lieux d’amélioration continue des projets ; promouvoir, voire même outiller, le recours à la mémoire de projet, même ponctuel, en particulier une mémoire centrée sur le processus (pour compléter celle, classique, centrée sur les résultats) et réalisée par tous les acteurs projet, y compris eux-mêmes.A major issue for ergonomists and preventionists is to have the project process evolve in order to effectively influence the design of work situations. This article discusses a continuous project-improvement mechanism that they could use to advantage to support their efforts : project memory. First, this article summarizes what is being said about this tool in the literature from the fields of project and organization management. It then proposes, to ergonomic and OHS professionals, lessons to be drawn from the project memory to support their design integration efforts : infiltrating the continuous project improvement activities that are taking place in the day-to-day life of the organization ; promoting the implementation of project memory practices, even sporadically, particularly process-oriented memory (to complement the more classical result-oriented memory) and carried out by all the project participants, including themselves.Para los ergonomistas y los especialistas en prevención, la evolución de la gestión de proyectos para poder influir eficazmente en la concepción de las situaciones de trabajo constituye un desafío mayor. Este artículo trata de un mecanismo de mejora continua de los proyectos que prodrían explotar para más eficacia en el apoyo de sus esfuerzos : la memoria de proyecto. Primero, el artículo resume lo que se dice de este instrumento en la literatura procediente de los ámbitos de la gestión de proyecto y de las organizaciones. Luego, propone, a los especialisatas en ergonomía y en SST, enseñanzas de la memoria de proyecto para apoyar sus esfuerzos de integración en la concepción : infiltrarse en los lugares de mejora continua de los proyectos ; promover, sino instrumentar el recurso a la memoria de proyecto, incluso puntual, en particular una memoria centrada en el proceso (para completar la memoria más clásica centrada en los resultados) y realizada por todos los actores del proyecto, incluso ellos mismos

Glucose management for exercise using continuous glucose monitoring (CGM) and intermittently scanned CGM (isCGM) systems in type 1 diabetes: position statement of the European Association for the Study of Diabetes (EASD) and of the International Society for Pediatric and Adolescent Diabetes (ISPAD) endorsed by JDRF and supported by the American Diabetes Association (ADA)

Physical exercise is an important component in the management of type 1 diabetes across the lifespan. Yet, acute exercise increases the risk of dysglycaemia, and the direction of glycaemic excursions depends, to some extent, on the intensity and duration of the type of exercise. Understandably, fear of hypoglycaemia is one of the strongest barriers to incorporating exercise into daily life. Risk of hypoglycaemia during and after exercise can be lowered when insulin‐dose adjustments are made and/or additional carbohydrates are consumed. Glycaemic management during exercise has been made easier with continuous glucose monitoring (CGM) and intermittently scanned continuous glucose monitoring (isCGM) systems; however, because of the complexity of CGM and isCGM systems, both individuals with type 1 diabetes and their healthcare professionals may struggle with the interpretation of given information to maximise the technological potential for effective use around exercise (ie, before, during and after). This position statement highlights the recent advancements in CGM and isCGM technology, with a focus on the evidence base for their efficacy to sense glucose around exercise and adaptations in the use of these emerging tools, and updates the guidance for exercise in adults, children and adolescents with type 1 diabetes

The time is now: Achieving FH paediatric screening across Europe – The Prague Declaration

ReviewFamilial Hypercholesterolaemia (FH) is severely under-recognized, under-diagnosed and under-treated in Europe, leading to a significantly higher risk of premature cardiovascular diseases in those affected. FH stands for inherited, very high cholesterol and affects 1:300 individuals regardless of their age, race, sex, and lifestyle, making it the most common inherited metabolic disorder and a non-modifiable cardiovascular disease risk factor in the world..info:eu-repo/semantics/publishedVersio

Consensus Recommendations for the Use of Automated Insulin Delivery (AID) Technologies in Clinical Practice

International audienceThe significant and growing global prevalence of diabetes continues to challenge people with diabetes (PwD), healthcare providers and payers. While maintaining near-normal glucose levels has been shown to prevent or delay the progression of the long-term complications of diabetes, a significant proportion of PwD are not attaining their glycemic goals. During the past six years, we have seen tremendous advances in automated insulin delivery (AID) technologies. Numerous randomized controlled trials and real-world studies have shown that the use of AID systems is safe and effective in helping PwD achieve their long-term glycemic goals while reducing hypoglycemia risk. Thus, AID systems have recently become an integral part of diabetes management. However, recommendations for using AID systems in clinical settings have been lacking. Such guided recommendations are critical for AID success and acceptance. All clinicians working with PwD need to become familiar with the available systems in order to eliminate disparities in diabetes quality of care. This report provides much-needed guidance for clinicians who are interested in utilizing AIDs and presents a comprehensive listing of the evidence payers should consider when determining eligibility criteria for AID insurance coverage

Automation of dictation exercises. A working combination of CALL and NLP.

This article is in the context of the Computer-Assisted Language Learning (CALL) frame- work, and addresses more specifically the automation of dictation exercises. It presents a method for correcting learners' copies. Based around Natural Language Processing (NLP) tools, this method is original in two respects. First, it exploits the composition of finite- state machines, to both detect and delimit the errors. Second, it uses automatic morpho- syntactic analysis of the original dictation, which makes it easier to produce superficial and in-depth linguistic feedback. The system has been evaluated on a corpus of 115 copies including 1,532 copy errors. The accuracy of the error detection is 99%. The superficial feedback is 97.2% correct, the in-depth feedback 96%, and the morpho-syntactic analysis 87.7%

Linguistic features weighting for a Text-To-Speech system without prosody model

4 pagesThis paper presents a Non-Uniform Units selection-based Text-To-Speech synthesizer. Nowadays, systems use prosodic models that do not allow the prosody to vary as far as we should hope, involving a listening comfort degradation. Our system has the advantage to avoid the using of prosodic model. Speech units selection builds its features set exclusively from the linguistic information generated by the natural language analysis. We also present an original method to automatically weight these features. Therefore, selected units are not restricted by a predetermined prosody. With only using linguistic features, we obtain a various prosody and the units concatenation is performed without resort to heavy signal processin

Synthèse vocale par sélection linguistiquement orientée d'unités non-uniformes : LiONS

Colloque avec actes et comité de lecture. nationale.National audienceCe papier présente un nouveau système de synthèse vocale à partir du texte, basé sur la sélection d'unités non-uniformes. Actuellement, les systèmes de synthèse utilisent des modèles prosodiques ce qui ne permet pas à la prosodie de varier autant que l'on puisse l'espérer, impliquant ainsi une perte de confort d'écoute. Notre système possède l'avantage d'éviter le recours à un modèle prosodique. La sélection d'unités de parole est conduite à partir d'un ensemble de caractéristiques exclusivement linguistiques obtenues par analyse du langage naturel. Nous présentons aussi une méthode originale de pondération automatique de ces caractéristiques. Au final, les unités sélectionnées ne sont pas restreintes par une prosodie pré-déterminée. Les caractéristiques linguistiques ont prouvé leur efficacité : nous obtenons une prosodie variée et la concaténation des unités est réalisée quasiment sans traitement du signal. || This paper presents a new Non-Uniform Units selection-based Text-To-Speech synthesizer. Nowadays, systems use prosodic models that do not allow the prosody to vary as far as we should hope, involving a listening comfort degradation. Our system has the a

Le TAL au service de l’ALAO/ELAO. L’exemple des exercices de dictée automatisés.

Ce papier s’inscrit dans le cadre général de l’Apprentissage et de l’Enseignement des Langues Assistés par Ordinateur, et concerne plus particulièrement l’automatisation des exercices de dictée. Il présente une méthode de correction des copies d’apprenants qui se veut originale en deux points. Premièrement, la méthode exploite la composition d’automates à états finis pour détecter et pour analyser les erreurs. Deuxièmement, elle repose sur une analyse morphosyntaxique automatique de l’original de la dictée, ce qui facilite la production de diagnostics.This paper comes within the scope of the Computer Assisted Language Learning framework, and addresses more especially the automation of dictation exercises. It presents a correction method of learners’ copies that is original in two ways. First, the method exploits the composition of finite-state automata, to both detect and analyze the errors. Second, it relies on an automatic morphosyntactic analysis of the original dictation, which makes it easier to produce diagnoses