Networked cooperation-based distributed model predictive control using Laguerre functions for large-scale systems

International audienceThis paper proposes a novel cooperative distributed control system architecture based on unsupervised and independent Model Predictive Control (MPC) using discrete-time Laguerre functions to improve the performance of the whole system. In this distributed framework, local MPCs algorithms might exchange and require information from other sub-controllers via the communication network to achieve their task in a cooperative way. In order to reduce the computational burden in the local rolling optimization with a sufficiently large prediction horizon, the orthonormal Laguerre functions are used to approximate the predicted control trajectory. Simulation results show that the proposed architecture could guarantee satisfactory global performance even under strong interactions among the subsystems

Etude de Faisabilité des Mécanismes de Détection de Mauvais Comportement dans les systèmes de transport intelligents coopératifs (C-ITS)

International audience—Cooperative Intelligent Transport Systems (C–ITS) is an emerging technology that aims at improving road safety, traffic efficiency and drivers experience. To this end, vehicles cooperate with each others and the infrastructure by exchanging Vehicle–to–X communication (V2X) messages. In such communicating systems message authentication and privacy are of paramount importance. The commonly adopted solution to cope with these issues relies on the use of a Public Key Infrastructure (PKI) that provides digital certificates to entities of the system. Even if the use of pseudonym certificates mitigate the privacy issues, the PKI cannot address all cyber threats. That is why we need a mechanism that enable each entity of the system to detect and report misbehaving neighbors. In this paper, we provide a state-of-the-art of misbehavior detection methods. We then discuss their feasibility with respect to current standards and law compliance as well as hardware/software requirements

Towards a Reliable Machine Learning Based Global Misbehavior Detection in C-ITS: Model Evaluation Approach

International audienceGlobal misbehavior detection in Cooperative Intelligent Transport Systems (C-ITS) is carried out by a central entity named Misbe-havior Authority (MA). The detection is based on local misbehavior detection information sent by Vehicle's On-Board Units (OBUs) and by RoadSide Units (RSUs) called Misbehavior Reports (MBRs) to the MA. By analyzing these Misbehavior Reports (MBRs), the MA is able to compute various misbehavior detection information. In this work, we propose and evaluate different Machine Learning (ML) based solutions for the internal detection process of the MA. We show through extensive simulation and several detection metrics the ability of solutions to precisely identify different misbehavior types

A Misbehavior Authority System for Sybil Attack Detection in C-ITS

International audienceGlobal misbehavior detection is an important back-end mechanism in Cooperative Intelligent Transport Systems (C-ITS). It is based on the local misbehavior detection information sent by Vehicle's On-Board Units (OBUs) and by RoadSide Units (RSUs) called Misbehavior Reports (MBRs) to the Mis-behavior Authority (MA). By analyzing these reports, the MA provides more accurate and robust misbehavior detection results. Sybil attacks pose a significant threat to the C-ITS systems. Their detection and identification may be inaccurate and confusing. In this work, we propose a Machine Learning (ML) based solution for the internal detection process of the MA. We show through extensive simulation that our solution is able to precisely identify the type of the Sybil attack and provide promising detection accuracy results

Viruses and Human Cancers: a Long Road of Discovery of Molecular Paradigms

About a fifth of all human cancers worldwide are caused by infectious agents. In 12% of cancers, seven different viruses have been causally linked to human oncogenesis: Epstein-Barr virus, hepatitis B virus, human papillomavirus, human T-cell lymphotropic virus, hepatitis C virus, Kaposi's sarcoma herpesvirus, and Merkel cell polyomavirus. Here, we review the many molecular mechanisms of oncogenesis that have been discovered over the decades of study of these viruses. We discuss how viruses can act at different stages in the complex multistep process of carcinogenesis. Early events include their involvement in mutagenic events associated with tumor initiation such as viral integration and insertional mutagenesis as well as viral promotion of DNA damage. Also involved in tumor progression is the dysregulation of cellular processes by viral proteins, and we describe how this has been investigated by studies in cell culture and in experimental animals and by molecular cellular approaches. Also important are the molecular mechanisms whereby viruses interact with the immune system and the immune evasion strategies that have evolved

Genetic affinities of Fusarim spp. and their correlation with origin and pathogenicity

Random amplified polymorphic DNA (RAPD) analyses was used in combination with pathogenicity assays to study the taxonomic kinships among five Fusarium species. A total of 46 isolates of Fusarium spp. obtained from diseased cotton seedlings showing typical root rot and dampping-off symptoms were characterized. Of 10 primers tested, four primers produced polymorphic amplification patterns with taxon-specific bands, in addition to individual-specific bands. Genetic analysis indicated into 2 main clusters, with the minor cluster included all F. moniliforme and F. solani at the genetic similarity of GS=57.82%. The major cluster consisted of all F. oxysporum, F. avenaceum and F. chlamydosporum clustered at 71% similarity. There was no clear-cut relationship between clustering in the RAPD dendrogram, pathogenicity test and geographic origin of tested isolates. The results suggest that RAPD-PCR is a useful method for analysing genetic variation within and between Fusarium spp. (African Journal of Biotechnology: 2003 2(5): 109-113

Molecular phylogeny of Fusarium species by AFLP fingerprint

The high-resolution genotyping method of amplified fragment length polymorphism (AFLP) analysis was used to study the genetic relationships within and between natural populations of five Fusarium spp. AFLP templates were prepared by the digestion of Fusarium DNA with EcoRI and MseI restriction endonucleases and subsequent ligation of corresponding site-specific adapters. An average of 44 loci was assayed simultaneously with each primer pair and DNA markers in the range 100 to 500 bp were considered for analysis. A total of 80 AFLP polymorphic markers were obtained using four primer combinations, with an average of 20 polymorphic markers observed per primer pair. UPGMA analyses indicated 5 distinct clusters at the phenon line of 30% on the genetic similarity scale corresponding to the 5 taxa. The similarity percent of each group oscillated between 87 and 97%. The phenetic dendrogram generated by UPGMA as well as principal coordinate analysis (PCA) grouped all of the Fusarium spp. isolates into five major clusters. No clear trend was detected between clustering in the AFLP dendrogram and geographic origin, host genotype of the tested isolates with a few exceptions. The results of the present study provide evidence of the high discriminatory power of AFLP analysis, suggesting the possible applicability of this method to the molecular characterization of Fusarium. (African Journal of Biotechnology: 2003 2(3): 51-55

PCR identification of Fusarium genus based on nuclear ribosomal-DNA sequence data

We have developed two taxon-selective primers for quick identification of the Fusarium genus. These primers, ITS-Fu-f and ITS-Fu-r were designed by comparing the aligned sequences of internal transcribed spacer regions (ITS) of a range of Fusarium species. The primers showed good specificity for the genus Fusarium, and the approximately 389-bp product was amplified exclusively. PCR sensitivity ranged from 100 fg to 10 ng for DNA extracted from Fusarium oxysporum mycelium. No amplification products were detected with PCR of DNA from Rhizoctonia solani and Macrophomina phaseolina isolates using these primers. The assay is useful for rapid identification of Fusarium spp. cultures. The application of these PCR methods for early diagnosis of the seedling and wilt disease of cotton needs to be studied further. (African Journal of Biotechnology: 2003 2(4): 82-85