Novel Lightweight Hydraulic Integration Methodology for Robotic Applications

International audienceHydraulic integration is one of the novel technologies in the field of robotics and assistive devices. Researchers have applied recent technologies starting from non-conventional machining methodologies and ending with additive manufacturing of metals. However, those methodologies have several drawbacks related to the cost, time, and robot weight. This motivates the research of new methodologies toward developing compact, cost-effective, and lightweight hydraulic integrated robotics mechanisms. This paper presents a novel methodology for fabricating hydraulically integrated parts by using lightweight and high-strength materials. The proposed materials, fabrication steps and the obtained results are thoroughly discussed. Silicon pipes are used for building the network of internal passages. This network is built inside a 3D-printed mould which is designed accordingly. A theoretical study is conducted for the newly manufactured hydraulic parts to define the design parameters and the working pressure at which the manufactured parts can withstand in addition to stresses and deformations analysis. The theoretical results are validated using finite element modelling (FEM) and experimental testing. The simulation results were consistent with the FEM results and the experimental results by 95% and 90% respectively. The proposed methodology is cheap and simple to implement in fabrication. Hence, this methodology can be used to fabricate hydraulic integrated components in hydraulically actuated humanoid robots successfully

A knowledge-centric model for government-orchestrated digital transformation among the microbusiness sector

FNEGE 2, HCERES A, ABS 4International audienceMost prior public sector digital transformation (DT) research has examined the role of digitalization in improving either the internal operational efficiency of the government or the quality of government service delivery to external stakeholders such as citizens and businesses. Although policy-driven digitalization of specific sectors is key for promoting public value, government’s role in orchestrating extra-government digitalization initiatives to create public value has not been sufficiently investigated. To address this perceptible void in the public sector DT literature, we study a government-led DT program designed to promote digitalization among microbusinesses (MB), a sector that has major economic and social implications. Given the significant role of technical and business knowledge in facilitating enterprise DT, we examine and theorize different knowledge mechanisms through which government policy initiatives can help foster MBs’ DT. Drawing on qualitative data from a series of structured interviews and focus groups with government agents, digital champions, and MB owner-managers involved in the implementation of a government-led DT program for MBs in Ireland, among the different DT stakeholders, we identify three knowledge pathways playing different knowledge-related roles and aiming to facilitate this transformation: top-down, bottom-up, and multidirectional. Each pathway comprises distinct practices. Collectively, the identified knowledge mechanisms in the DT program knowledge ecosystem foster social value creation for both MBs and government stakeholders, and therefore for the nation as a whole. Specifically, sustenance of the DT program is achieved through “initiation” and “instantiation” knowledge routes. Our findings offer theoretical contributions to the literatures on government-led digital transformations, effectiveness of government-led digital initiatives, and digital transformation in the MB sector. Our study also has significant implications for policy and practice

Stability analysis of conformable fractional order systems

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Ce que les appels à projets du Plan d’investissement dans les compétences font à l’accompagnement vers l’emploi

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Prescribed-Time Adaptive Fuzzy Optimal Control for Nonlinear Systems

International audienceThe prescribed-time optimal control problem for nonlinear systems is investigated in this paper. First, a transformation function is constructed, which includes the system state and a strictly decreasing auxiliary function related to the prescribed time and accuracy. Second, the control input and the transformation function are incorporated into a new performance index function (PIF). This encodes the prescribed-time control into the optimal control problem. Subsequently, a new Hamilton-Jacobi-Bellman (HJB) equation related to the prescribed time and accuracy is derived. To find a solution to the HJB equation, a fuzzy reinforcement learning algorithm is proposed. This algorithm successfully approximates the optimal cost and control policy while ensuring the system stability. Additionally, the system state can converge to a pre-assigned residual set within a prescribed time. Finally, an example of an electromechanical system is used to illustrate the efficacy of the suggested algorithm

Identifier de nouvelles cibles moléculaires pour mieux comprendre la maladie de Parkinson

Poster vulgarisé à destination du public dans le cadre des journées Park'coeur organisées par France Parkinso

Uno sguardo complice. Martine Franck e il movimento delle donne

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The crucial role of IT identity in employee advocacy platforms

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Pollutant Concentration Prediction by Random Forest to Estimate a Contaminant Source Position

International audienceThe goal of Source Term Estimation (STE) is to accurately identify the parameters that describe the source of a release, namely the position and strength . This requires a reliable dispersion model. Recent advancements have integrated machine learning with the Gaussian dispersion model, enhancing the prediction of pollutant concentrations while mitigating the impact of complex terrains. However, pollutant dispersion varies significantly across different atmospheric stability classes. Addressing this, we introduce a novel strategy termed the Multiple Learning Model (MLM), which segments predictions based on stability classes: Neutral (), Unstable (), and Stable (). This approach, by building models to specific atmospheric conditions, promises more precise source estimations. In comparative study, MLM not only refined prediction accuracy from 0.04 to 0.06 but also improved source location estimates, narrowing the discrepancy to 7 m–25 m from the actual source, a marked improvement over traditional random forest models. This methodological advancement underscores the potential of stability-class-specific models in enhancing the accuracy and reliability of pollutant source estimations

Sense-remaking: unpacking ethical judgment change in a Business Ethics course

FNEGE 2, HCERES A, ABS 1International audienceWhile business ethics (BE) courses have increasingly formed part of business school curricula, we still do not know much about how these courses can change students’ capacity to deal with ethical issues. Drawing on a sensemaking perspective, we conducted an action research study with 66 business professionals enrolled in an executive training program at a French university. The aim was to investigate the processes underlying ethical judgment (EJ) change through a BE course. Participants were invited to pick a significant ethical issue they had personally experienced at work. They were then asked to make sense of it, in writing, at the beginning and at the end of the course, 3 months later. In comparing pre-course and post-course judgments, we concluded that the structure and contents of the respondents’ initial judgment had indeed been modified. This change could be accounted for as the outcome of four ‘sense-remaking’ mechanisms, which we theorize as complexifying, reprioritizing, conceptualizing and contextualizing. Our study contributes to the literature on BE education by demonstrating the benefits of a sensemaking approach. It also offers an original process-based model of EJ, specifying the mechanisms at play in EJ change. Finally, it contributes to the field of sensemaking studies by introducing the concept of sense-remaking, shedding new light on the evolutive dimension of sensemaking