Portail HAL des publications du LIRMM
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Inspector Gadget
No full textInspectorGadget is a tool designed to obtain an estimate of the performance and the memory cost of masking gadgets
One Health in practice: a socio-ecological approach for the study and management of zoonoticdiseases associated with free-roaming dogs in Southeast Asia (SEAdogSEA)
No full textInternational audienceFree-roaming domestic dogs are widespread in SE Asia, occurring in most biomes and interacting with human commensals in many diverse ways. Major public health threats in the region are associated with dogs, but their role in the epidemiology of numerous other zoonotic diseases is still unknown.This depends on a complex interplay between ecological drivers associated with dogs and the habitats in which they roam, and socio-anthropological parameters associated with the humans with whom they interact.The interdisciplinary projects SEAdogSEA associated several teams from Europe and SE Asia(2019/2023), with the aim to study dog-human-environment interactions and associatedepidemiological risks in four villages selected in three countries: Thailand (Nan province), Indonesia(Bali), and Cambodia (Kandal and Stung Treng provinces).Three main interdisciplinary protocols were carried out: i) Monitoring dog movements and habitat use, mobilising ecology (GPS collars) and socio-anthropology; ii) Assessing dog contact patterns using camera-traps images analysed by Artificial Intelligence for dog re-identification; iii) Pathogen screening (arboviruses, ectoparasites and blood parasites, leptospirosis, …) and microbiome analysis in dog/dog-owner paired samples.We present selected results illustrating the complex interplay between dogs’ ecology, owners’ socialcharacteristics and occupation, and the associated risks of zoonotic diseases (e.g. typology of dogmovements/spatial behaviour). Recommendations are given for a more (than) One Health management of sanitary risks associated with domestic dogs in rural and semi-urban settings in SEAsia, including a discussion on the potential use of domestic dogs as sentinels/indicators of theinfectious risks to which their owners are exposed
Coupling microfabrication, electronics and tissue engineering to study skeletal muscle physiology
No full textInternational audienc
BiodivPortal: Enabling Semantic Services for Biodiversity within the German National Research Data Infrastructure
No full textInternational audienceResearch has become increasingly reliant on extensive data. The integration, sharing and reuse of research data poses a significant challenge, particularly in the context of interdisciplinary collaborative projects. An essential objective for a research infrastructure dedicated to data management is to facilitate efficient data discovery and integration of diverse data sources. This pressing need for FAIR data requires, besides persistent identifiers and data citation rules, common standards and shared vocabularies, thesauri and ontologies. These knowledge artifacts, referred to as terminologies, often exist in disconnected and distributed forms. The work presented in this paper describes our terminology repository and service, enabling a unified access, development, and maintenance of terminologies within biodiversity and environmental sciences. We characterize use cases requirements for semantically enhanced components and applications and show where the adoption of the OntoPortal technology enabled us to cover those requirements in the context of our research infrastructure
Weighted majority vote using Shapley values in crowdsourcing
No full textInternational audienceCrowdsourcing has emerged as a pivotal paradigm for harnessing collective intelligence to solve data annotation tasks. Effective label aggregation, crucial for leveraging the diverse judgments of contributors, remains a fundamental challenge in crowdsourcing systems. This paper introduces a novel label aggregation strategy based on Shapley values, a concept originating from cooperative game theory. By integrating Shapley values as worker weights into the Weighted Majority Vote label aggregation (WMV), our proposed framework aims to address the interpretability of weights assigned to workers. This aggregation reduces the complexity of probabilistic models and the difficulty of the final interpretation of the aggregation from the workers' votes. We show improved accuracy against other WMV-based label aggregation strategies. We demonstrate the efficiency of our strategy on various real datasets to explore multiple crowdsourcing scenarios
Multi-level Analysis of GPU Utilization in ML Training Workloads
No full textInternational audienceTraining time has become a critical bottleneck due 100% to the recent proliferation of large-parameter ML models. GPUs continue to be the prevailing architecture for training ML models. However, the complex execution flow of ML frameworks makes it difficult to understand GPU computing resource utilization. Our main goal is to provide a better understanding of how efficiently ML training workloads use the computing resources of modern GPUs. To this end, we first describe an ideal reference execution of a GPU-accelerated ML training loop and identify relevant metrics that can be measured using existing profiling tools. Second, we produce a coherent integration of the traces obtained from each profiling tool. Third, we leverage the metrics within our integrated trace to analyze the impact of different software optimizations (e.g., mixed-precision, various ML frameworks, and execution modes) on the throughput and the associated utilization at multiple levels of hardware abstraction (i.e., whole GPU, SM subpartitions, issue slots, and tensor cores). In our results on two modern GPUs, we present seven takeaways and show that although close to 100% utilization is generally achieved at the GPU level, average utilization of the issue slots and tensor cores always remains below 50% and 5.2%, respectively
M4.2 - Processes & tools to engineer FAIR semantic artefacts
No full textIn this milestone, we propose a FAIR by design methodology for developing ontologies that could be extended to address other types of semantic artefacts. That is, the work developed for and reported in this milestone focuses on semantic artefacts (mostly vocabularies and ontologies) formalised in the RDF(S) and OWL representation languages mainly
Mise en place les téléconsultations par les sages-femmes pendant la crise sanitaire du COVID-19 : étude par méthode mixte
No full textInternational audienc
SoftED: Metrics for Soft Evaluation of Time Series Event Detection
No full textInternational audienceTime series event detection methods are evaluated mainly by standard classification metrics that focus solely on detection accuracy. However, inaccuracy in detecting an event can often result from its preceding or delayed effects reflected in neighboring detections. These detections are valuable to trigger necessary actions or help mitigate unwelcome consequences. In this context, current metrics are insufficient and inadequate for the context of event detection. There is a demand for metrics that incorporate both the concept of time and temporal tolerance for neighboring detections. This paper introduces SoftED metrics, a new set of metrics designed for soft evaluating event detection methods. They enable the evaluation of both detection accuracy and the degree to which their detections represent events. They improved event detection evaluation by associating events and their representative detections, incorporating temporal tolerance in over 36% of experiments compared to the usual classification metrics. SoftED metrics were validated by domain specialists that indicated their contribution to detection evaluation and method selection
Citizen science platforms can effectively support early detection of invasive alien species according to species traits
No full textInternational audienceEarly detection and rapid response are essential to deal effectively with new introductions of invasive alien species (IAS). Citizen science platforms for opportunistic recording of species are increasingly popular, and there is potential to harvest their data for early detection of IAS, but this has not been tested. We evaluated the potential of data from existing citizen science platforms for early detection of IAS by obtaining 687 first records of species from 30 European countries where there was both an official first record (i.e. published in scientific literature or by a government agency) and a record in a citizen science platform. We tested how the difference between the two (time lag) was related to species traits, popularity in citizen science platforms, public and research attention and regulatory status. We found that for 50% of the time lag records, citizen science platforms reported IAS earlier than or in the same year as the official databases. Although we cannot determine causality (the first official record could have been from a citizen science platform, or contemporaneous with it), this demonstrates that citizen science platforms are effective for IAS early detection. Time lags were largely affected by species traits. Compared with official records, vertebrates were more likely to have earlier records on citizen science platforms, than plants or invertebrates. Greater popularity of the IAS in citizen science platforms and its observation in neighbouring countries resulted in earlier citizen science reporting. In contrast, inclusion in the EU priority list resulted in earlier official recording, reflecting the efficacy of targeted surveillance programmes. However, time lags were not affected by the overall activity of citizen platforms per country. Synthesis and applications: Multi‐species citizen science platforms for reporting nature sightings are a valuable source of information on early detection of IAS even though they are not specifically designed for this purpose. We recommend that IAS surveillance programmes should be better connected with citizen science platforms, including greater acknowledgement of the role of citizen scientists and better data flow from smaller citizen science initiatives into global databases, to support efficient early detection