Hybridation of Bayesian networks and evolutionary algorithms for multi-objective optimization in an integrated product design and project management context

A better integration of preliminary product design and project management processes at early steps of system design is nowadays a key industrial issue. Therefore, the aim is to make firms evolve from classical sequential approach (first product design the project design and management) to new integrated approaches. In this paper, a model for integrated product/project optimization is first proposed which allows taking into account simultaneously decisions coming from the product and project managers. However, the resulting model has an important underlying complexity, and a multi-objective optimization technique is required to provide managers with appropriate scenarios in a reasonable amount of time. The proposed approach is based on an original evolutionary algorithm called evolutionary algorithm oriented by knowledge (EAOK). This algorithm is based on the interaction between an adapted evolutionary algorithm and a model of knowledge (MoK) used for giving relevant orientations during the search process. The evolutionary operators of the EA are modified in order to take into account these orientations. The MoK is based on the Bayesian Network formalism and is built both from expert knowledge and from individuals generated by the EA. A learning process permits to update probabilities of the BN from a set of selected individuals. At each cycle of the EA, probabilities contained into the MoK are used to give some bias to the new evolutionary operators. This method ensures both a faster and effective optimization, but it also provides the decision maker with a graphic and interactive model of knowledge linked to the studied project. An experimental platform has been developed to experiment the algorithm and a large campaign of tests permits to compare different strategies as well as the benefits of this novel approach in comparison with a classical EA

Amélioration des techniques d'optimisation combinatoire par retour d'expérience dans le cadre de la sélection de scénarios de Produit/Projet

La définition et l’utilisation d'un modèle couplant la conception de produit et la conduite du projet dès les phases amont de l’étude d’un système correspondent à une forte demande industrielle. Ce modèle permet la prise en compte simultanée de décisions issues des deux environnements produit/projet mais il représente une augmentation conséquente de la dimension de l'espace de recherche à explorer pour le système d'aide à la décision, notamment lorsque il s'agit d'une optimisation multiobjectif. Les méthodes de type métaheuristique tel que les algorithmes évolutionnaires, sont une alternative intéressante pour la résolution de ce problème fortement combinatoire. Ce problème présente néanmoins une particularité intéressante et inexploitée : Il est en effet courant de réutiliser, en les adaptant, des composants ou des procédures précédemment mis en œuvre dans les produits/projets antérieurs. L'idée mise en avant dans ce travail consiste à utiliser ces connaissances « a priori » disponibles afin de guider la recherche de nouvelles solutions par l'algorithme évolutionnaire. Le formalisme des réseaux bayésiens a été retenu pour la modélisation interactive des connaissances expertes. De nouveaux opérateurs évolutionnaires ont été définis afin d'utiliser les connaissances contenues dans le réseau. De plus, le système a été complété par un processus d'apprentissage paramétrique en cours d'optimisation permettant d'adapter le modèle si le guidage ne donne pas de bons résultats. La méthode proposée assure à la fois une optimisation plus rapide et efficace, mais elle permet également de fournir au décideur un modèle de connaissances graphique et interactif associé au projet étudié. Une plateforme expérimentale a été réalisée pour valider notre approche. ABSTRACT : The definition and use of a model coupling product design and project management in the earliest phase of the study of a system correspond to a keen industrial demand. This model allows simultaneous to take into account decisions resulting from the two environments (product and project) but it represents a consequent increase of the search space dimension for the decision-making system, in particular when it concerns a multiobjective optimization. Metaheuristics methods such as evolutionary algorithm are an interesting way to solve this strongly combinative problem. Nevertheless, this problem presents an interesting and unexploited characteristic: It is indeed current to re-use, by adapting them, the components or the procedures previously implemented in pasted product or project. The idea proposed in this work consists in using this “a priori” knowledge available in order to guide the search for new solutions by the evolutionary algorithm. Bayesian network was retained for the interactive modeling of expert knowledge. New evolutionary operators were defined in order to use knowledge contained in the network. Moreover, the system is completed by a process of parametric learning during optimization witch make it possible to adapt the model if guidance does not give good results. The method suggested ensures both a faster and effective optimization, but it also makes it possible to provide to the decision maker a graphic and interactive model of knowledge linked to studied project. An experimental platform was carried out to validate our approach

Parcellation of fMRI datasets with ICA and PLS: a data driven approach

Inter-subject parcellation of functional Magnetic Resonance Imaging (fMRI) data based on a standard General Linear Model (GLM) and spectral clustering was recently proposed as a means to alleviate the issues associated with spatial normalization in fMRI. However, for all its appeal, a GLM-based parcellation approach introduces its own biases, in the form of a priori knowledge about the shape of Hemodynamic Response Function (HRF) and task-related signal changes, or about the subject behaviour during the task. In this paper, we introduce a data-driven version of the spectral clustering parcellation, based on Independent Component Analysis (ICA) and Partial Least Squares (PLS) instead of the GLM. First, a number of independent components are automatically selected. Seed voxels are then obtained from the associated ICA maps and we compute the PLS latent variables between the fMRI signal of the seed voxels (which covers regional variations of the HRF) and the principal components of the signal across all voxels. Finally, we parcellate all subjects data with a spectral clustering of the PLS latent variables. We present results of the application of the proposed method on both single-subject and multi-subject fMRI datasets. Preliminary experimental results, evaluated with intra-parcel variance of GLM t-values and PLS derived t-values, indicate that this data-driven approach offers improvement in terms of parcellation accuracy over GLM based techniques

What is the difference between irony and sarcasm? An fMRI study

Verbal irony is a figure of speech that communicates the opposite of what is said, while sarcasm is a form of irony that is directed at a person, with the intent to criticise. The current study used functional magnetic resonance imaging (fMRI) with the aim of mapping the neural networks involved in the processing of sarcastic and non-sarcastic irony. Participants read short texts describing an interaction between two characters, which ended in either a literal, sarcastic, or non-sarcastic ironic comment. Results showed that the mentalising network (mPFC) and semantic network (IFG) were more activated for non-sarcastic irony than for literal controls. This would suggest that interpreting this kind of language involves understanding that the speaker does not mean what they literally say, as well as processes involved in conflict detection and resolution. Sarcastic irony recruited more of the semantic network, as well as areas associated with humour appreciation and subcortical structures, indicating that more complex neural mechanisms underlie the comprehension of sarcastic versus non-sarcastic irony

The timing mega-study: comparing a range of experiment generators, both lab-based and online

Many researchers in the behavioral sciences depend on research software that presents stimuli, and records response times, with sub-millisecond precision. There are a large number of software packages with which to conduct these behavioural experiments and measure response times and performance of participants. Very little information is available, however, on what timing performance they achieve in practice. Here we report a wide-ranging study looking at the precision and accuracy of visual and auditory stimulus timing and response times, measured with a Black Box Toolkit. We compared a range of popular packages: PsychoPy, E-Prime®, NBS Presentation®, Psychophysics Toolbox, OpenSesame, Expyriment, Gorilla, jsPsych, Lab.js and Testable. Where possible, the packages were tested on Windows, macOS, and Ubuntu, and in a range of browsers for the online studies, to try to identify common patterns in performance. Among the lab-based experiments, Psychtoolbox, PsychoPy, Presentation and E-Prime provided the best timing, all with mean precision under 1 millisecond across the visual, audio and response measures. OpenSesame had slightly less precision across the board, but most notably in audio stimuli and Expyriment had rather poor precision. Across operating systems, the pattern was that precision was generally very slightly better under Ubuntu than Windows, and that Mac OS was the worst, at least for visual stimuli, for all packages. Online studies did not deliver the same level of precision as lab-based systems, with slightly more variability in all measurements. That said, PsychoPy and Gorilla, broadly the best performers, were achieving very close to millisecond precision on several browser/operating system combinations. For response times (measured using a high-performance button box), most of the packages achieved precision at least under 10 ms in all browsers, with PsychoPy achieving a precision under 3.5 ms in all. There was considerable variability between OS/browser combinations, especially in audio-visual synchrony which is the least precise aspect of the browser-based experiments. Nonetheless, the data indicate that online methods can be suitable for a wide range of studies, with due thought about the sources of variability that result. The results, from over 110,000 trials, highlight the wide range of timing qualities that can occur even in these dedicated software packages for the task. We stress the importance of scientists making their own timing validation measurements for their own stimuli and computer configuration

Piecewise Affine Registration of Biological Images for Volume Reconstruction

This manuscript tackles the reconstruction of 3D volumes via mono-modal registration of series of 2D biological images (histological sections, autoradiographs, cryosections, etc.). The process of acquiring these images typically induces composite transformations that we model as a number of rigid or affine local transformations embedded in an elastic one. We propose a registration approach closely derived from this model. Given a pair of input images, we first compute a dense similarity field between them with a block matching algorithm. We use as a similarity measure an extension of the classical correlation coefficient that improves the consistency of the field. A hierarchical clustering algorithm then automatically partitions the field into a number of classes from which we extract independent pairs of sub-images. Our clustering algorithm relies on the Earth mover’s distribution metric and is additionally guided by robust least-square estimation of the transformations associated with each cluster. Finally, the pairs of sub-images are, independently, affinely registered and a hybrid affine/non-linear interpolation scheme is used to compose the output registered image. We investigate the behavior of our approach on several batches of histological data and discuss its sensitivity to parameters and noise

Sarah Hatchuel, Rêves et séries américaines. La fabrique d’autres mondes

D’emblée, soulignons le grand plaisir que procure la lecture de cet ouvrage qui ravira tout amateur de séries télévisées, que ce soit dans le cadre privé ou dans celui de la recherche universitaire. Les chercheurs apprécieront la grande finesse d’analyses particulièrement éclairantes quant aux ressorts narratifs, esthétiques et idéologiques des fictions télévisées sérielles et à leur réception, ainsi que les nombreuses sources tant primaires que secondaires et la bibliographie riche et claire..

Jocelyn Dupont, Gilles Menegaldo, Spectres de Poe dans la littérature et dans les arts

Quand en exergue de l’avant-propos de l’ouvrage on lit Baudelaire avouant : « son fantôme m’a toujours obsédé », se pose d’emblée la question, quel fantôme ? Celui de Poe, celui de ses personnages, de son écriture ou des atmosphères qu’il a créées ? Les vingt-trois essais qui constituent cet ouvrage, issus d’un colloque organisé au Centre Culturel International de Cerisy-la-Salle au cours de l’été 2017, nous permettent de revenir aux sources de cette obsession puis d’explorer ses formes et de..

Representative Benchmark for Concurrent Product and Process Configuration Problem: Definitions and Some Problem Instances

International audienceThis paper considers the Optimization of Concurrent Product and Process Configuration problems (O-CPPC) that satisfy various number of criteria, which rely on the customer’s requirements and the objectives of the company. Various works have proposed evolutionary optimization algorithms dedicated to this concurrent configuration problem with generic model propositions due to this paper is relevant to the evaluation of these optimization algorithms. The aim of this paper is to define a set of instances of the generic model that represent a large family of problems. First, a background of the Optimization of Concurrent Product and Process Configuration problems is introduced. Next, some basic definitions of an O-CPPC generic model are analyzed. Then, the main general parameters to define an instance are presented (Product Structure, Process Structure, Model Size and Model Constraint Density) in order to propose some general evaluation tests. And finally, to be consistent with the previous works, some basic cases are described to show how to deal with this kind of problem in an organized way

Plan de Actuación de un Departamento de Orientación : uso de la Gamificación en el Programa de Diversidad Curricular

El Programa de Diversificación Curricular (PDC) se caracteriza por una atención más personalizada al alumnado en comparación con un aula ordinaria, gracias su ratio más reducido. Este programa tiene como objetivo que aquel alumnado que tenga dificultades pueda titular. Sin embargo, a pesar de las diferencias con las aulas ordinarias, el alumnado sigue con unos niveles bajos de motivación hacia los estudios. Por ello, tras una revisión de las teorías de la motivación, así como una revisión sobre los beneficios de la gamificación, con el fin de aumentar los niveles de motivación del alumnado de estos programas, y trabajar diferentes habilidades socioemocionales, se propone un plan de actuación mediante el uso de la gamificación en los diferentes ámbitos y asignaturas en los que se divide el currículo del PDC.The Curricular Diversification Programme (CDP) is known to have a more personalised attention to students compared to an ordinary classroom, thanks to its smaller ratio. The programme´s aim is to help those with mayor difficulties to graduate. However, despite the differences with the ordinary classrooms, students continue to have low levels of motivation towards their studies. Therefore, after a review of the theories of motivation, as well as a review of the benefits of gamification, in order to increase the motivation levels of students in these programmes, and to work on various socioemotional skills, an action plan is proposed using gamification in the different areas and subject into which the curriculum of the CDP is divided.Máster Universitario en Formación del Profesorado de ESO, Bachillerato, Formación Profesional y Enseñanza de Idiomas. Especialidad en Orientación Educativa (M089