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A direct adaptive control architecture for buildings thermal comfort and energy efficiency optimization using multilayer perceptron neural networks and model reference learning
No full textInternational audienceThis paper presents an original direct adaptive control strategy applied to a building heating system, using an intelligent control approach based on Multi-Layer Perceptron (MLP) neural networks. The main contribution of this work is the integration of a newly developed climate database, representing the coldest regions of Algeria, into the Simbad simulation environment. This enhancement significantly increases the realism and robustness of the simulation, allowing for a more accurate assessment of control performance under extreme and challenging climate conditions. The proposed control architecture follows a model reference structure in which an MLP-based adaptive controller ensures real-time adjustment to varying thermal demands and external disturbances. Unlike conventional fixed-parameter controllers, the system learns and adapts online to maintain thermal comfort while optimizing energy usage. Simulation results demonstrate the effectiveness of the proposed method in achieving precise temperature regulation and substantial energy savings. This study highlights the importance of coupling intelligent control techniques with realistic environmental data to develop energy-efficient solutions tailored to diverse climatic contexts
Use of Sensors in Rehabilitation of Patients Undergoing Knee Arthroplasty: A Systematic Review
No full textInternational audienceAims: To characterize the use of inertial sensors for assessing mobility, function, and gait in patients undergoing unilateral knee arthroplasty for advanced osteoarthritis. Study Design: Systematic review. Place and Duration of Study: Searches were performed in PubMed, Embase, Scopus and Web of Science databases with no restrictions on date, language, or disease severity. Study selection was completed in 2025. Searches were last performed in 2025. Methodology: This review was registered with PROSPERO (CRD420251002284) and conducted according to PRISMA guidelines. Two independent reviewers screened titles, abstracts, and full texts using predefined inclusion and exclusion criteria. Risk of bias was assessed using a 10-item adapted Downs & Black scale. Data on study populations, experimental protocols, and gait parameters were extracted and synthesized descriptively. Results: Twenty-one cross-sectional studies were included, comprising 758 patients post-TKA and approximately 210 healthy controls. Inertial sensors ranged from 1 to 15 units, most placed on the lower back or pelvis. Walking protocols spanned 6–40 m courses, treadmill tests, oval circuits, and "free-living" monitoring. The primary parameters collected were spatiotemporal (speed, cadence, step length, phase durations) and kinematic (knee joint angles and pelvis/trunk movements). Studies demonstrated good reliability (ICC > 0.85) and accuracy (< 5° angular error). None explicitly investigated differences by prosthesis type. Findings reveal persistent spatiotemporal deficits and kinematic alterations following TKA. Conclusion: Wearable inertial sensors appear to be valid and feasible tools for capturing mobility, function, and gait outcomes after knee arthroplasty. However, substantial methodological heterogeneity (e.g., sensor placement, sampling rates, assessment protocols, and outcome definitions) limits cross-study comparability and precluded meta-analysis. Standardization of protocols and improved reporting, together with higher-quality comparative studies (including evaluation of implant design effects), are priorities to support clinical implementation
Documenting the Challenges of the Late Antique Miaphysite Church
No full textInternational audienceThe earliest history of the miaphysite church is extraordinarily rich in documents. This volume asks why and how the Miaphysite Church produced such an extraordinary theological, canonical and historical documentation? In order to make these collections more accessible for future historians, contributors study the make-up of the collections, the images that they project, their transmission and translation, and what kind of information they provide for modern historians
Evaluating experimental design to sample mosquitoes
No full textInternational audienceMosquito study is crucial for public health, research, and vector control. We evaluated four understudied aspects of experimental design: (i) global efficiency of trapping devices—BG-Sentinel (BG) vs. CDC light traps (LT), (ii) temporal efficiency over a three-day sampling period, (iii) the impact of sampling duration on vector presence and abundance assessments, and (iv) site visit frequency for biodiversity surveys. Both traps were deployed across 10 Cambodian provinces, with collections conducted every 24 h over three-day periods from 2019 to 2021. A total of 1992 collections yielded 181,798 mosquitoes spanning 153 identified species. Using a hurdle generalized linear mixed model to address overdispersion and zero inflation, we found that 21 of 54 studied species showed a preference for one of the trapping device: LT captured 15 species more efficiently, while six species preferred BG. Anthropophilic vectors such as Aedes aegypti and Aedes albopictus were more attracted to BG, whereas LT captured higher species richness and zoophilic vectors. For six of 13 primary vector species, we showed that the capture efficiency declines from day one to day three on a three days sampling period. However, annual trends in presence and abundance remained consistent regardless of whether sampling lasted one, two, or three days. Finally, we quantified the probability of collecting a new species during subsequent visits, showing that this probability declines with visit sampling effort at rates dependent on trap type and sampling days duration. These findings provide empirical guidelines for optimizing mosquito surveillance strategies based on study objectives
The Impact of Continuous Glucose Monitoring on Glycaemic Control in Children with Type 1 Diabetes: A Systematic Review
No full textInternational audienceThe management of type 1 diabetes mellitus (T1DM) in a paediatric population represents an ongoing clinical challenge, requiring precise and sustainable strategies for glycaemic monitoring. Traditional capillary monitoring, although essential, presents significant limitations, including discomfort and an inability to detect rapid fluctuations. In this context, continuous glucose monitoring (CGM) has emerged as a promising technology capable of overcoming these barriers. This systematic review aimed to synthesise the evidence regarding the effectiveness of CGM in glycaemic control in children with T1DM, as well as to evaluate its performance in comparison with conventional capillary monitoring. To this end, a systematic review was conducted in accordance with PRISMA guidelines, including searches across multiple databases (PubMed, Scopus, Web of Science, SciELO, BVS, Google Scholar, and CAPES Journals), which resulted in the identification of 109 studies, of which 54 met the inclusion criteria. These studies demonstrated that CGM achieved a modest yet significant reduction in HbA1c levels, alongside a marked decrease in the frequency of severe and nocturnal hypoglycaemia, and a substantial improvement in glycaemic variability. A positive impact on quality of life was also observed, with reduced parental anxiety and greater autonomy for children. Thus, it is concluded that continuous glucose monitoring constitutes an effective tool for enhancing glycaemic control in children with type 1 diabetes, offering benefits that extend beyond HbA1c optimisation and include improved metabolic safety and psychosocial well-being. However, it is important to emphasise that successful implementation depends on integrating the technology into a comprehensive care model that is also centred on the child’s family
Un changement d'affectation peut être effectué dans l'intérêt du service pour mettre fin à des difficultés d'ordre relationnel
No full textInternational audienceNote sous CAA Marseille, 12 novembre 2024, no 24MA0032
Fault Detection in Gearboxes Using Fisher Criterion and Adaptive Neuro-Fuzzy Inference
No full textInternational audienceGearboxes are autonomous devices essential for power transmission in various mechanical systems. When a failure occurs, it can lead to an inability to perform the required functions, potentially resulting in a complete shutdown of the mechanism and causing significant operational disruptions. Consequently, deploying expert methods for fault detection and diagnosis is crucial to ensuring the reliability and efficiency of these systems. Artificial intelligence (AI) techniques show promise for fault diagnosis, but their accuracy can be hindered by noise and manufacturing imperfections that distort mechanical signatures. Thorough data analysis and preprocessing are vital to preserving these critical features. Validating approaches through numerical simulations before experimentation is essential to identify model limitations and minimize risks. A hybrid approach, combining AI and physics-based models, could provide a robust solution by leveraging the strengths of both domains: AI for its ability to process large volumes of data and physics-based models for their reliability in modeling complex mechanical behaviors. This paper proposes a comprehensive diagnostic methodology. It starts with feature extraction from time-domain analysis, which helps identify critical indicators of gearbox performance. Following this, a feature selection process is applied using the Fisher criterion, which ensures that only the most relevant features are retained for further analysis. These selected features are then employed to train an Adaptive Neuro-Fuzzy Inference System (ANFIS), a sophisticated approach that combines the learning capabilities of neural networks with the reasoning abilities of fuzzy logic. The proposed methodology is evaluated using a dataset of gear faults generated through energy simulations based on a six-degree-of-freedom (6-DOF) model, followed by a secondary validation on an experimental dataset
