Pierre Collet

Andrés Bello University | UNAB · ITISB

The El Niño-Southern Oscillation (ENSO) significantly influences the complexity and variability of the global climate system, driving its variability. ENSO events’ irregularity and unpredictability arise from intricate ocean–atmosphere interactions and nonlinear feedback mechanisms, complicating their prediction of timing, intensity, and geographic...

Medical acts, such as imaging, lead to the production of various medical text reports that describe the relevant findings. This induces multimodality in patient data by combining image data with free-text and consequently, multimodal data have become central to drive research and improve diagnoses. However, the exploitation of patient data is probl...

Accurate forecasting of the baccalaureate admission statistics is a crucial step towards an improvement of the educational system in Mauritania and its responsiveness to the economical needs. Since an available historical information is collected only over last ten years, an accurate forecasting technique for short time series is required. Addressi...

As the size of quantum hardware progressively increases, the conjectured computational advantages of quantum technologies tend to be threatened by noise, which randomly corrupts the design of quantum logical gates. Several methods already exist to reduce the impacts of noise on that matter. However, a reliable and user-friendly one to reduce the no...

The widespread use of high throughput genome sequencing technologies has resulted in a significant increase in the number of available sequences, creating new challenges for genome annotation and prediction of protein-coding genes in terms of error detection and quality control. Multiple Sequence Alignments (MSAs) of the predicted protein sequences...

Skeletal muscle structure can differ depending on the specie or type of muscle. For example, deltoid, diaphragm, tibialis anterior and gastrocnemius muscles have different morphological features (Burdi et al, 2009; Rafael et al, 1994; Piñol-Jurado et al, 2018). In addition, several myopathies affect only a subset of skeletal muscles with no particu...

Multiple Sequence Alignments set the basis for many biological sequence analysis methods. However, they are susceptible to irregularities that result either from the predicted sequences or from natural biological events. In this paper, we propose MERLIN (Msa ERror Localization and IdentificatioN), an object detector that consists in identifying suc...

Anticipatory Learning Classifier Systems (ALCS) are rule-based machine learning algorithms that can simultaneously develop a complete representation of their environment and a decision policy based on this representation to solve their learning tasks. This paper introduces BEACS (Behavioral Enhanced Anticipatory Classifier System) in order to handl...

Background Medical acts, such as imaging, generally lead to the production of several medical text reports that describe the relevant findings. Such processes induce multimodality in patient data by linking image data to free-text data and consequently, multimodal data have become central to drive research and improve diagnosis of patients. However...

Background Ab initio prediction of splice sites is an essential step in eukaryotic genome annotation. Recent predictors have exploited Deep Learning algorithms and reliable gene structures from model organisms. However, Deep Learning methods for non-model organisms are lacking. Results We developed Spliceator to predict splice sites in a wide rang...

Complexity is commonly summarized as ‘the actions of the whole are more than the sum of the actions of the parts’. Understanding how the coherence emerges from these natural and artificial systems provides a radical shift in the process of thought, and brings huge promises for controlling and fostering this emergence. The authors define the term ‘C...

Quantum-inspired algorithms are efficient for solving global search optimization problems. Nevertheless, their application is limited by two main requirements: a knowledge of a cost function and a big computational effort. To address both limitations, this paper presents a global optimization algorithm mixing a Quantum Diffusion Monte Carlo (DMC) m...

Background Recent advances in sequencing technologies have led to an explosion in the number of genomes available, but accurate genome annotation remains a major challenge. The prediction of protein-coding genes in eukaryotic genomes is especially problematic, due to their complex exon–intron structures. Even the best eukaryotic gene prediction alg...

This papers introduces BACS, a learning classifier system that integrates Behavioral Sequences to ACS2 (Anticipatory Classifier System 2), in order to address the Perceptual Aliasing Issue: this issue occurs when systems can not differentiate situations that are truly distinct in partially observable environments. In order to permit this integratio...

Background. Recent advances in sequencing technologies have led to an explosion in the number of genomes available, but accurate genome annotation remains a major challenge. The prediction of protein-coding genes in eukaryotic genomes is especially problematic, due to their complex exon-intron structures. Even the best eukaryotic gene prediction al...

Background. Recent advances in sequencing technologies have led to an explosion in the number of genomes available, but accurate genome annotation remains a major challenge. The prediction of protein-coding genes in eukaryotic genomes is especially problematic, due to their complex exon-intron structures. Even the best eukaryotic gene prediction al...

Background: Recent advances in sequencing technologies have led to an explosion in the number of genomes available, but accurate genome annotation remains a major challenge. The prediction of protein-coding genes in eukaryotic genomes is especially problematic, due to their complex exon-intron structures. Even the best eukaryotic gene prediction al...

This paper proposes a fast evolutionary algorithm for large-scale multi-objective optimization problems (MOPs), which widely exist in real-world applications [3, 6]. Many well-established multi-objective evolutionary algorithms (MOEAs) can not ensure necessary Runtime (RT) and values of performance metrics (Hypervolume (HV), Inverted Generational D...

Background: The draft genome assemblies produced by new sequencing technologies present important challenges for automatic gene prediction pipelines, leading to less accurate gene models. New benchmark methods are needed to evaluate the accuracy of gene prediction methods in the face of incomplete genome assemblies, low genome coverage and quality...

Background: The draft genome assemblies produced by new sequencing technologies present important challenges for automatic gene prediction pipelines, leading to less accurate gene models. New benchmark methods are needed to evaluate the accuracy of gene prediction methods in the face of incomplete genome assemblies, low genome coverage and quality,...

Background: The draft genome assemblies produced by new sequencing technologies present important challenges for automatic gene prediction pipelines, leading to less accurate gene models. New benchmark methods are needed to evaluate the accuracy of gene prediction methods in the face of incomplete genome assemblies, low genome coverage and quality,...

Detecting anomalies in time series in real time can be challenging, in particular when anomalies can manifest themselves at different time scales and need to be detected with minimal latency. The need for lightweight real-time algorithms has risen in the context of Cloud computing, where thousands of devices are monitored and deviations from normal...

Storing sensitive data in a centralized way can lead to significant loss, should the central node or networks links be defective as is the case in numerous countries, especially developing countries. Consequently, this paper proposes to deal with this problem by diluting sensitive data into an ecosystem of machines thanks to a platform called RADAR...

Behind firewalls, more and more cybersecurity attacks are specifically targeted to the very network where they are taking place. This review proposes a comprehensive framework for addressing the challenge of characterising novel complex threats and relevant counter-measures. Two kinds of attacks are particularly representative of this issue: zero-d...

The rapid evolution of IT ecosystems significantly challenges the security models our infrastructures rely on. Beyond the old dichotomy between open and closed systems, it is now necessary to handle securely the interaction between heterogeneous devices building dynamic ecosystems. To this regard, bio-inspired approaches provide a rich set of conce...

Cohort Study Platforms (CSP) are emerging as a key tool for collecting patient information, providing new research data, and supporting family and patient associations. However they pose new ethics and regulatory challenges since they cross the gap between patients and medical practitioners. One of the critical issues for CSP is to enforce a strict...

In this chapter, the authors show how knowledge engineering techniques can be used to guide the definition of evolutionary algorithms (EA) for problems involving a large amount of structured data, through the resolution of a real problem. Various representations of the fitness functions, the genome, and mutation/crossover operators adapted to diffe...

In this paper, we propose a new approach to the performance supervision of complex and heterogeneous infrastructures found in hybrid cloud networks, which typically consist of hundreds or thousands of interconnected servers and networking devices. This hardware and the quality of the interconnections are monitored by sampling specific metrics (such...

This paper describes the Collaborative Open Peer Assessment formative evaluation proposed by the POEM Personalised Open Education for the Masses platform of the Complex Systems Digital Campus UNESCO UniTwin. COPA allows teachers to use open questions and answers to assess the level of the great number of students that is typical of Massive Open Onl...

Path planning for surgical tools in minimally invasive surgery is a multi-objective optimization problem consisting in searching the best compromise between multiple placement constraints to find an optimal insertion point for the tool. Many works have been proposed to automate the decision-making process. Most of them use an aggregative approach t...

Artificial Immune Systems bear two complementary radical insights for building immune properties into technical systems: AIS algorithms, which have proved their efficiency for anomaly detection, and what we call Artificial Immune Ecosystems, i.e. distributed architectures capable of decentralised sensing, analysis and reactions to these anomalies....

The advent of the Big Data hype and the consistent recollection of event logs and real-time data from sensors, monitoring software and machine configuration has generated a huge amount of time-varying data in about every sector of the industry. Rule-based processing of such data has ceased to be relevant in many scenarios where anomaly detection an...

One of the challenges in machine learning, especially in the Big Data era, is to obtain labeled data sets. Indeed, the difficulty of labeling large amounts of data had lead to an increasing reliance on unsupervised classifiers, such as deep autoencoders. In this paper, we study the problem of involving a human expert in the training of a classifier...

Evolutionary algorithms (EAs) are inherently parallel, because they evolve a population of distinct individuals in a generational loop. These algorithms are therefore very good candidates to be ported on massively multicore architectures. EAsy Specification of EA (EASEA) is a software platform dedicated to EAs that allows to exploit parallel archit...

This book contains the proceedings as well as invited papers for the first annual conference of the UNESCO Unitwin Complex System Digital Campus (CSDC), which is an international initiative gathering 120 Universities on four continents, and structured in ten E-Departments. First Complex Systems Digital Campus World E-Conference 2015 features chapte...

Zeolite structure determination and zeolite framework generation are not new problems but due to the increasing computer power, these problems came back and they are still a challenge despite the recent progress in terms of structural resolution from X-rays and electron diffraction. The infinite number of potential solutions and the computational c...

Preoperative path planning for Deep Brain Stimulation (DBS) is a multi-objective optimization problem consisting in searching the best compromise between multiple placement constraints. Its automation is usually addressed by turning the problem into mono-objective thanks to an aggregative approach. However, despite its intuitiveness, this approach...

This paper presents the first implementation of NSGA-II in neurosurgery preoperative path planning. Deep Brain Stimulation (DBS) is a surgical treatment of Parkinson's disease that can be regarded as a multi-objective optimization problem, searching for the best compromise between multiple electrode placement rules. Most of the current automatic de...

Synthetic biology aims at reinvesting theoretical knowledge from various do-mains (biology, engineering, microelectronics) for the development of new bio-logical functions. Concerning the design of such functions, the classical trial-error approach is expensive and time consuming. Computer-aided design is therefore of key interest in this field. As...

Evolutionary Algorithms (EA) have proven to be very effective in optimizing intractable problems in many areas. However, real problems including specific constraints are often overlooked by the proposed generic models. The authors' goal here is to show how knowledge engineering techniques can be used to guide the definition of Evolutionary Algorith...

The problem of the transportation of patients from or to some health care center given a number of vehicles of different kinds can be considered as a common Vehicle Routing Problem (VPR). However, in our particular case, the logistics behind the generation of the vehicle itineraries are affected by a high number of requirements and constraints such...

The Lean Organisation enjoys a tremendous success. It was first developed within Toyota Motor Corporation in the Automotive Industry, but was then adopted by many organisations in all fields of human activities. A deeper observation of this success displays behaviours of complex systems: a high number of agents interact with each other, using basic...

In this paper, we propose a new approach to the performance supervision of complex and heterogeneous infrastructures found in hybrid cloud networks, which typically consist of hundreds or thousands of interconnected servers and networking devices. This hardware and the quality of the interconnections is monitored by sampling specific metrics (such...

The Lean Organisation enjoys a tremendous success. It was first developed within Toyota Motor Corporation in the Automotive Industry, but was then adopted by many organisations in all fields of human activities. A deeper observation of this success displays behaviours of complex systems: a high number of agents interact with each other, using basic...

Cette communication décrit la procédure d'évaluation participative pair à pair P 3 E (Participative Peer-To-Peer Evaluation) de la plate-forme POEM (Personalised Open Education for the Masses) développée à l'Université de Strasbourg dans le cadre du Complex Systems Digital Campus, réseau UniTwin de l'UNESCO comportant 115 universités dans le monde....

This work presents a method to evaluate the quality of candidate models for a given observed system in terms of fitness. Taking a candidate model, i.e. a proposed differential equation, this work uses the Galerkin method with a Jacobi/Legendre polynomial basis to approximate solve it. After, this method computes the mean square error between the ap...

This work proposes and presents a preliminary investigation of a fitness evaluation scheme supported by a proper genotype representation intended to guide an under development expansion to EASEA/EASEA-CLOUD platforms to evolve partial differential equations as models for a specific system of interest, starting with measures from that system. A simp...

Pour assurer la surveillance des SI « de gestion » ou industriels, les SIEM actuels reposent sur un modèle de type NAC qui traite les évènements émis par les sondes de surveillance (logs) à la façon de flux « big-data » : variés, variables, denses et structurés. Or, de nombreux évènements issus d’attaques complexes ciblées ne présentent pas de stru...

Monitoring and visualisation tools are currently attracting more and more attention in order to understand how search spaces are explored by complex optimisation ecosystems such as parallel evolutionary algorithms based on island models. Multilevel visualisation is actually a desirable feature for facilitating the monitoring of computationally expe...

Su-Field analysis, as one of the inventive problem solving tools, can be used to analyze and improve the efficiency of a technical system. Generally, the process of using Su-Field models to solve a specific inventive problem includes building a Problem Model, mapping to a Generic Problem Model (the abstract Problem Model to describe the Problem Mod...

Agility for IT project management, especially the SCRUM framework, lays on a systemic approach to management. We strongly believe that a thorough understanding of complex system concepts behind SCRUM will highlight success factors, thereby empowering practitioners with a comprehensive framework for leading their projects to full achievement. We dep...

Swarming has become a management tool for letting individuals cooperate in order to generate emergent solutions to difficult issues in organizations. Beyond the buzzword, we claim that swarming actually matches specific project manage-ment practices having a great potential for improving project success. Swarming project management is defined, and...