Cergy, France
Cergy, France
Time filter
Source Type

Nguyen N.,EISTI Cergy | Mhenni F.,Quartz Laboratory | Choley J.Y.,Quartz Laboratory
Risk, Reliability and Safety: Innovating Theory and Practice - Proceedings of the 26th European Safety and Reliability Conference, ESREL 2016 | Year: 2017

Redundancy or the use of additional components in a safety-critical system is mandatory to improve its reliability. It is important for system engineers to integrate redundancy-relevant information in the early design stages. This facilitates safety analyses by ensuring consistency between systems engineering and safety analysis activities, thus reducing errors and time-to-market. © 2017 Taylor & Francis Group, London.

Gardeux V.,EISTI Cergy | H. Omran M.G.,Gulf | Chelouah R.,EISTI Cergy | Siarry P.,University Paris Est Creteil | Glover F.,University of Colorado at Boulder
Applied Intelligence | Year: 2017

The emergence of high-dimensional data requires the design of new optimization methods. Indeed, conventional optimization methods require improvements, hybridization, or parameter tuning in order to operate in spaces of high dimensions. In this paper, we present a new adaptive variant of a pattern search algorithm to solve global optimization problems exhibiting such a character. The proposed method has no parameters visible to the user and the default settings, determined by almost no a priori experimentation, are highly robust on the tested datasets. The algorithm is evaluated and compared with 11 state-of-the-art methods on 20 benchmark functions of 1000 dimensions from the CEC’2010 competition. The results show that this approach obtains good performances compared to the other methods tested. © 2017 Springer Science+Business Media New York

Boyd A.D.,University of Illinois at Chicago | Li J.J.,University of Illinois at Chicago | Burton M.D.,University of Illinois at Chicago | Jonen M.,University of Illinois at Chicago | And 9 more authors.
Journal of the American Medical Informatics Association | Year: 2013

Objective: Applying the science of networks to quantify the discriminatory impact of the ICD-9-CM to ICD-10-CM transition between clinical specialties. Materials and Methods: Datasets were the Center for Medicaid and Medicare Services ICD-9-CM to ICD-10-CM mapping files, general equivalence mappings, and statewide Medicaid emergency department billing. Diagnoses were represented as nodes and their mappings as directional relationships. The complex network was synthesized as an aggregate of simpler motifs and tabulation per clinical specialty. Results: We identified five mapping motif categories: identity, class-to-subclass, subclass-to-class, convoluted, and no mapping. Convoluted mappings indicate that multiple ICD-9-CM and ICD-10-CM codes share complex, entangled, and non-reciprocal mappings. The proportions of convoluted diagnoses mappings (36% overall) range from 5% (hematology) to 60% (obstetrics and injuries). In a case study of 24 008 patient visits in 217 emergency departments, 27% of the costs are associated with convoluted diagnoses, with 'abdominal pain' and 'gastroenteritis' accounting for approximately 3.5%. Discussion: Previous qualitative studies report that administrators and clinicians are likely to be challenged in understanding and managing their practice because of the ICD-10-CM transition. We substantiate the complexity of this transition with a thorough quantitative summary per clinical specialty, a case study, and the tools to apply this methodology easily to any clinical practice in the form of a web portal and analytic tables. Conclusions: Post-transition, successful management of frequent diseases with convoluted mapping network patterns is critical. The http://lussierlab.org/transition-to- ICD10CM web portal provides insight in linking onerous diseases to the ICD-10 transition.

Barot S.,Ecole Normale Superieure de Paris | Bornhofen S.,EISTI Cergy | Loeuille N.,University Paris Diderot | Perveen N.,French National Institute for Agricultural Research | And 2 more authors.
Journal of Ecology | Year: 2014

It is important to study how evolution impacts on plant functional traits and to determine how this subsequently determines ecosystem functioning. We tackle this general issue by studying the evolution of plant strategies that affect mineralization through the chemical quality of their own litter and their position on the leaf economic spectrum. This spectrum allows us to classify all plants on a single axis ranging from resource-acquisitive to resource-conservative strategies. We build a spatially explicit and individual-based simulation model: individual plants grow in the cells of a lattice and the limiting nutrient is recycled locally in these cells. Individual plants may die and produce seeds that are dispersed. Mutants with different mineralization strategies appear stochastically. A trade-off is implemented between the rate of nutrient loss from plants and litter mineralization. In the spatial-explicit model, plant capacity to increase mineralization evolves and reaches an evolutionary equilibrium in most cases. The evolved mineralization decreases with plant longevity, seed dispersal efficiency, spatial homogenization of mineral nutrient availability and inputs of mineral nutrient to the ecosystem. The evolved mineralization strategies neither maximize plant biomass, nor minimize the availability of mineral nutrient or the stock of dead organic matter. The evolutionary and ecological impacts of nutrient enrichment on the stock of organic matter are different. Synthesis. Our results suggest that plant mineralization strategy may evolve provided that the mineral resource is not fully shared by all individuals. Such an evolution modifies soil capacity to store organic carbon thereby being relevant in the context of the current climate change and global nutrient enrichment. Indeed, our model shows that evolutionary feedbacks of plants to nutrient enrichment are likely to differ from purely ecological feedbacks. Our results suggest that plant mineralization strategy may evolve provided that the mineral resource is not fully shared by all individuals. Such an evolution modifies soil capacity to store organic carbon thereby being relevant in the context of the current climate change and global nutrient enrichment. Indeed, our model shows that evolutionary feedbacks of plants to nutrient enrichment are likely to differ from purely ecological feedbacks. © 2014 British Ecological Society.

Mhenni F.,ISMEP | Nguyen N.,EISTI Cergy | Choley J.-Y.,ISMEP
IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM | Year: 2014

In this paper, a methodology is proposed to integrate safety analysis within a systems engineering approach. This methodology is based on SysML models and aims at generating (semi-) automatically safety analysis artifacts, mainly FMEA and FTA, from system models. Preliminary functional and component FMEA are automatically generated from the functional and structural models respectively, then completed by safety experts. By representing SysML structural diagram as a directed multi-graph, through a graph traversal algorithm and some identified patterns, generic fault trees are automatically derived with corresponding logic gates and events. The proposed methodology provides the safety expert with assistance during safety analysis. It helps reducing time and error proneness of the safety analysis process. It also helps ensuring consistency since the safety analysis artifacts are automatically generated from the latest system model version. The methodology is applied to a real case study, the electromechanical actuator EMA. © 2014 IEEE.

Arib S.,EISTI Cergy | Aknine S.,University Claude Bernard Lyon 1 | Cazenave T.,University of Paris Dauphine
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2015

This paper develops and evaluates a coalition mechanism that enables agents to participate in concurrent tasks achievement in competitive situations in which agents have several constraints. Here we focus on situations in which the agents are self-interested and have not a priori knowledge about the preferences of their opponents, and they have to cooperate in order to reach their goals. All the agents have their specific constraints and this information is private. The agents negotiate for coalition formation (CF) over these constraints, that may be relaxed during negotiations. They start by exchanging their constraints and m aking proposals, which represent their acceptable solutions, until either an agreement is reached, or the negotiation terminates.We explore two techniques that ease the search of suitable coalitions: we use a constraintbased model and a heuristic search method. We describe a procedure that transforms these constraints into a structured graph on which the agents rely during their negotiations to generate a graph of feasible coalitions. This graph is therefore explored by a Nested Monte-Carlo search algorthm to generate the best coalitions and to minimize the negotiation time. © Springer International Publishing Switzerland 2015.

Gardeux V.,EISTI Cergy | Chelouah R.,EISTI Cergy | Siarry P.,University Paris Est Creteil | Glover F.,OptTek Systems, Inc.
Soft Computing | Year: 2011

This paper presents a performance study of a one-dimensional search algorithm for solving general high-dimensional optimization problems. The proposed approach is a hybrid between a line search algorithm of Glover (The 3-2-3, stratified split and nested interval line search algorithms. Research report, OptTek Systems, Boulder, CO, 2010) and an improved variant of a global method of Gardeux et al. (Unidimensional search for solving continuous high-dimensional optimization problems. In: ISDA '09: Proceedings of the 2009 ninth international conference on intelligent systems design and applications, IEEE Computer Society, Washington, DC, USA, pp 1096-1101, 2009) that uses line search algorithms as subroutines. The resulting algorithm, called EM323, was tested on 19 scalable benchmark functions, with a view to observing how optimization techniques for continuous optimization problems respond with increasing dimension. To this end, we report the algorithm's performance on the 50, 100, 200, 500 and 1,000-dimension versions of each function. Computational results are given comparing our method with three leading evolutionary algorithms. Statistical analysis discloses that our method outperforms the other methods by a significant margin. © 2010 Springer-Verlag.

Loubiere P.,EISTI Cergy | Jourdan A.,EISTI Cergy | Siarry P.,CNRS Laboratory of Image Signal and Intelligent Systems | Chelouah R.,EISTI Cergy
Applied Soft Computing Journal | Year: 2016

In this paper, we improve D. Karaboga's Artificial Bee Colony (ABC) optimization algorithm, by using the sensitivity analysis method described by Morris. Many improvements of the ABC algorithm have been made, with effective results. In this paper, we propose a new approach of random selection in neighborhood search. As the algorithm is running, we apply a sensitivity analysis method, Morris' OAT (One-At-Time) method, to orientate the random choice selection of a dimension to shift. Morris' method detects which dimensions have a high influence on the objective function result and promotes the search following these dimensions. The result of this analysis drives the ABC algorithm towards significant dimensions of the search space to improve the discovery of the global optimum. We also demonstrate that this method is fruitful for more recent improvements of ABC algorithm, such as GABC, MeABC and qABC. © 2016 Elsevier B.V. All rights reserved.

Malek M.,EISTI Cergy | Kadima H.,EISTI Cergy
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2013

We propose a new algorithm for searching frequent itemsets in large data bases. The idea is to start searching from a set of representative examples instead of testing the 1-itemset,the k-itemset and so on. A clustering algorithm is firstly applied in order to cluster the transactions into k clusters. The set of the k representative examples will be used as the starting point for searching frequent itemsets. Each cluster is represented by the most representative example. We show some preliminary results and we then propose a parallel version of this algorithm based on the MapReduce Framework. © 2013 Springer-Verlag.

Bornhofen S.,EISTI Cergy | Barot S.,Ecole Normale Superieure de Paris | Lattaud C.,University of Paris Descartes
Ecological Modelling | Year: 2011

This paper introduces a functional-structural plant model based on artificial life concepts and L-systems. This model takes into account realistic physiological rules, the architecture of the plants and their demography. An original benefit of this approach is that it allows the simulation of plant evolution at both functional and life-history levels implementing mutations to the L-systems and a set of genetic parameter values. The conducted experiments focus on the evolutionary emergence of different life history strategies in an environment with heterogeneous resource availability and disturbance frequency. It is found that, depending on the encountered conditions, the plants develop three major strategies classified as competitors, stress-tolerators and ruderals according to Grime's CSR theory. Most of the evolved characteristics comply with theoretical biology or field observations on natural plants. Besides these results, our modelling framework is highly flexible and many refinements can be readily implemented depending on the issues one intends to address. Moreover, the model can readily be used to address many questions at the interface between evolutionary ecology, plant functional and community ecologies and ecosystem ecology. © 2010 Elsevier B.V.

Loading EISTI Cergy collaborators
Loading EISTI Cergy collaborators