Aurélien Hazan

Université Paris-Est Créteil Val de Marne - Université Paris 12 | UPEC · Département Génie Electrique et Informatique Industrielle (S/F)

In this article, production process databases originating from environmental sciences, more specifically from Life Cycle Inventory (LCI), are considered as bipartite directed random networks. To model the observed directed hierarchical connection patterns, we turn to recent development concerning trophic coherence. Extending the scope to include bip...

We propose a network analysis of Life Cycle Inventory databases and show their hierarchical properties using trophic levels and trophic coherence. We verify that the number of cycles is correlated to trophic coherence, as predicted by the theory, and we propose some extensions in the bipartite case. Example in the food sector are tackled using the...

Dans cette présentation, nous étudions la base Lifi des participations financières entres entreprises françaises du point de vue de l'analyse des réseaux, et montrons une forte cohérence trophique des principales composantes connexes du réseau. Les explications disponibles dans la littérature sont comparées.

In this article, production process databases originating from environmental sciences, more specifically from Life Cycle Inventory (LCI), are considered as bipartite directed random networks. To model the observed directed hierarchical connection patterns, we turn to recent development concerning trophic coherence. Extending the scope to include bi...

In spite of rising climatic and environmental concern, modeling of Input-Output theory, Industrial Ecology, Life Cycle Assessment, and Material Flow Analysis are under-represented in complex networks research. To fill that gap we compare various network representations of interactions occurring in the aforementioned domains, and extending the scop...

In order to clarify the relationship between renormalizable network models and hierarchicalness, we elaborate on a recent binary fitness-based renormalizable network model and evaluate how it can cope with hierarchicalness, that was characterized in several ways in the literature, and remains an elusive concept. To do so a benchmark hierarchical ne...

A recent binary fitness-based renormalizable network models is fit to empir- ical networks across several levels. First, the case when a ”natural” hierarchical partition is available is examined, and examplified with trade data at a finer scale than in the original paper. The goodness of fit at a fixed level is compared to the output of established...

A recent binary fitness-based renormalizable network models is fit to empirical networks across several levels. First, the case when a "natural" hierarchical partition is available is examined, and examplified with trade data at a finer scale than in the original paper. The goodness of fit at a fixed level is compared to the output of established f...

We introduce a multidimensional, neural network approach to reveal and measure urban segregation phenomena, based on the self-organizing map algorithm (SOM). The multidimensionality of SOM allows one to apprehend a large number of variables simultaneously, defined on census blocks or other types of statistical blocks, and to perform clustering alon...

In this paper we analyze the origin-destination matrix arising from freight flows that occur in single-mode transport networks and compare unbiased maximum-entropy models of the corresponding networks. An original model based on earlier results allows to reconstruct a weighted network, from degree and strength sequences, taking distances into accou...

Input output analysis enables the study of dependences between industrial sectors, and to link final and intermediate demands. In this article, multiplicative perturbations are introduced in the input-output matrix. Approximate moments and pdf of the solution are studied using several techniques.

In this article the problem of reconstructing the pattern of connection between agents from partial empirical data in a macroeconomic model is addressed, given a set of behavioral equations. This systemic point of view puts the focus on distributional and network effects, rather than time-dependence. Using the theory of complex networks we compare...

We report on results concerning a partially aggregated Stock Flow Consistent (SFC) macroeconomic model in the stationary state where the sectors of banks and firms are aggregated, the sector of households is dis-aggregated, and the probability density function (pdf) of the wealth of households is exogenous, constrained by econometric data. It is sh...

We introduce a multidimensional, neural-network approach to reveal and measure urban segregation phenomena, based on the Self-Organizing Map algorithm (SOM). The multidimensionality of SOM allows one to apprehend a large number of variables simultaneously, defined on census or other types of statistical blocks, and to perform clustering along them....

Segregation phenomena have long been a concern for policy makers and urban planners, and much attention has been devoted to their study, especially in the fields of quantitative sociology and geography. Perhaps the most common example of urban segregation corresponds to different groups living in different neighbourhoods across a city, with very fe...

We show that a steady-state stock-flow consistent macroeconomic model can be represented as a Constraint Satisfaction Problem (CSP). The set of solutions is a polytope, which volume depends on the constraints applied and reveals the potential fragility of the economic circuit, with no need to specify the dynamics. Several methods to compute the vol...

An original novelty detection algorithm in the Fourier domain, using extreme value theory (EVT) is considered in this article. Periodograms may be considered as frequency-dependent random variables , and this can be taken into account when designing statistical tests. Frequency-Dependent Peak-Over-Threshold (FDPOT) puts special emphasis on the freq...

We study the behaviour of a Schelling-class system in which a fraction $f$ of spatially-fixed switching agents is introduced. This new model allows for multiple interpretations, including: (i) random, non-preferential allocation (\textit{e.g.} by housing associations) of given, fixed sites in an open residential system, and (ii) superimposition of...

The issue of detecting abnormal vibrations from spectra is tackled in this article, when little is known about the mechanical behavior of the system, or the fault pattern. To do so, an original algorithm relying on the statistics of the maximum of log-periodograms is introduced. Receiver Operator Char- acteristic (ROC) curves are built and show goo...

The issue of detecting abnormal vibrations from spectra is addressed in this article, when little is known both on the mechanical behavior of the system, and on the characteristic patterns of potential faults. With vibration measured from a bearing test rig and from an aircraft engine, we show that when only a small learning set is available, proba...

The issue of detecting abnormal vibrations is addressed in this article, when little is known both on the mechanical behavior of the system, and on the characteristic patterns of potential faults. With data from a bearing test rig and from an aircraft engine, we show that when only a small learning set is available, Bayesian inference has several a...

La compréhension des phénomènes économiques nécessite de prendre en compte plusieurs échelles de temps simultanément. Nous étudions le cas d'un modèle simple d'épargne, où plusieurs échelles de temps caractéristiques coexistent. Nous montrons qu'il est possible de séparer les contributions lentes et rapides confondues dans une même variable observé...

The problem of aircraft engine condition monitoring based on vibration signals is addressed. To do so, we compare two estimators of the Frequency Response Function of an aircraft engine which input is its shaft angular position and which output is an accelerometric signal that measures vibrations. It is shown that this problem can be seen as a smoo...

The automatic detection of the vibration signature of rotating parts of an aircraft engine is considered. This paper introduces an algorithm that takes into account the variation over time of the level of detection of orders, i.e. vibrations ate multiples of the rotating speed. The detection level over time at a specific order are gathered in a soc...

In this article we analyze several vibration time series measured on a real fan test rig before and after it is hit by a flying object. We show first evidence that a windowed autoregressive model may be used to detect the shock after it occurred. We compare these results with a second time series that measures the rotation period of the fan. Lastly...

The various scales of a signal maintain relations of dependence the on es with the others. Those can vary in time and reveal speed changes in the studied phenomenon. In the goal to establish these changes, one shall compute first the wavelet transform of a signal, on various scales. Then one shall study the statistical dependences between these tra...

With the objective of questioning the foundings of network modeling in complex systems sciences, this article addresses the issue of building discrete topological spaces from continuous data measured on a complex system thanks to sta- tistical inference, then to characterize the obtained space. We first take the example of graphs to underline the s...

We propose to classify the behaviors of a mobile robot thanks to topological methods as an alternative to metric ones. To do so, we adapt an analysis scheme from physics of nonlinear systems in chaotic regime, assuming a dissipative dynamics that relaxes on a low-dimensional manifold. Sensor data recorded from a mobile robot during a wall-following...

Through a Dynamical Systems approach to robotics, we introduce a measure of distinguishability between different behaviours of a robot, in an uncertain context, thanks to interval analysis.

In this article, we give some insights of a novel approach to active environment recognition in mobile robotics. The basic idea consists on utilizing a Physics-like interaction law to fix a relation between sensors and effectors values at any time. Our main assumption is that the trajectory of the robot in the phase space, which depends uniquely on...

The various scales of a signal maintain relations of dependence the ones with the others. Those can vary in time and reveal speed changes in the studied phenomenon. In the goal to establish these changes, one shall compute first the wavelet transform of a signal, on various scales. Then one shall study the statistical dependences between these tran...

Comment un robot peut-il estimer si une tâche est réalisable ou pas dans un envi ronnement donné ? De nombreux travaux en robotique s'appuient pour répondre sur les affordances de la psychologie écologique. Apprendre quelles sont les actions permises nécessite selon nous d'apprendre les relations de dépendances locales et globales entre capteurs et...