Feria artesanal de Plaza Italia : Un lugar conflictivo para el trabajo informal

Con el objetivo de analizar las características de la relación entre los vendedores ambulantes y los artesanos que comparten el espacio público dentro de la feria de Plaza Italia y sus consecuencias, en este trabajo se buscará analizar los discursos tanto de unos como de otros, determinar el rol de la municipalidad dentro de dicha relación y estudiar los reclamos y denuncias realizadas por los artesanos.Jornadas realizadas junto con el I Encuentro Latinoamericano de Metodología de las Ciencias Sociales.Facultad de Humanidades y Ciencias de la Educació

A Framework for the Performance Analysis and Simulation of RF-Mesh Advanced Metering Infrastructures for Smart Grid Applications

RÉSUMÉ L’Infrastructure de Mesurage Avancée (IMA), conçue à l’origine pour lire à distance des compteurs intelligents, est actuellement considérée comme une composante essentielle dans le domaine des Smart Grid. Le but principal des IMAs est de connecter le grand nombre de compteurs intelligents installés chez les clients au le centre de contrôle de données de l’entreprise d’électricité et viceversa. Cette communication bidirectionnelle est une caractéristique recherchée par un grand nombre d’applications, qui visent à utiliser ces infrastructures comme support à la transmission de leurs données dans le réseau électrique, comme par exemple la gestion de la charge et la demande-réponse. Un grand nombre de technologies et de protocoles de communication sont actuellement utilisés dans les IMAs : parmi les solutions disponibles, le RF-Mesh est une des plus populaires, surtout grâce au bas coût pour l’installation et les équipements. Toutefois, le débit nominal des communications RF-Mesh est très bas, de l’ordre des dizaines de kbps, et la littérature qui traite leur performance est très limitée. Ceci pourrait en limiter l’utilisation pour des applications autres que la lecture à distance des compteurs intelligents. Ce travail de thèse vise à développer un système de modèles et outils pour évaluer la performance des réseaux RF-Mesh et encourager leur utilisation pour un grand nombre d’applications dans le domaine des Smart Grid. Le système d’évaluation de performance proposé est constitué (i) de modèles analytiques, pour calculer la probabilité de collision entre les paquets transmis, (ii) d’un simulateur de réseau, pour recréer le fonctionnement des réseaux RF-Mesh dans un environnement virtuel, (iii) d’un générateur de topologie, pour créer des cas réalistes en se basant sur des données géographiques et (iv) des méthodes pour l’analyse de la performance. Trois différents modèles analytiques ont été implémentés. Dans les deux premiers, une nouvelle formule analytique a été utilisée pour calculer la probabilité de collision entre paquets. La probabilité de collision est ensuite utilisée pour estimer le délai moyen de/vers chaque compteur intelligent dans l’IMA analysée. Par la suite, des indices de performance, basés sur le délai moyen, sont utilisés pour faire des analyses de performance : études de faisabilité pour les applications de Smart Grid, l’identification de noeuds critiques et d’éventuels goulots d’étranglement. Dans le troisième modèle analytique, la théorie de Markov-Modulated System est utilisée pour prendre en considération d’importants détails d’implémentation, comme la probabilité de retransmission et la taille des mémoires tampons des noeuds, qui n’avaient pas été inclus dans la modélisations précédente.----------ABSTRACT Advanced Metering Infrastructure (AMI), originally conceived to replace the old Automated Meter Reading (AMR) infrastructures, have now become a key element in the Smart Grid context and might be used for applications other than remote meter reading. The main driver to their widespread installation is that they provide power utilities with a bidirectional connectivity with the smart meters. A wide variety of communication networks are currently proposed to support the implementation of AMIs, and, among them, the RF-Mesh technology seems to be very popular. The main reasons for its adoption are the proprietary infrastructure and the modest cost for the installation and the equipment. However, RF-Mesh systems are characterized by poor achievable data-rates in the order of 10 kbps, and their performance is not well studied in the literature. The lack of tools and methods for the performance evaluation might be a roadblock to their widespread adoption. This thesis aims at filling this gap and increase the knowledge of large-scale RF-Mesh systems to foster their use for a wide variety of applications. We propose a comprehensive framework for the performance evaluation of large-scale AMIs adopting the RF-Mesh technology. The framework includes (i) a geo-based topology generator that uses geographic data to produce realistic AMI cases, (ii) analytic models for the computation of packet collision probability and delay, (iii) a network simulator to recreate the behavior of large-scale RF-Mesh systems, and (iv) methods to evaluate the performance. Three different analytic models are included in the framework. The first two provide a novel analytic formulation of the packet collision probability in a mesh network with timeslotted ALOHA and the Frequency Hopping Spread Spectrum (FHSS) protocol : the collision probability is then used to estimate the average delay in the network, and to define and evaluate performance indexes (e.g., critical nodes and survival function). In the third model, a complex Markov-Modulated System (MMS) is used to take into consideration important implementation details, such as the retransmission probability and the buffer size, that were not considered in the two previous models. This model also provides a more accurate computation of the packet collision probability. A Poisson distribution is used to represent the traffic coming from potential Smart Grid applications. The framework also includes an RFMesh network simulator, written in Java and Python. The tool provides additional enhanced features with respect to the analytic models, such as a dynamic routing protocol or different traffic distributions

Synergies Between Federated Learning and O-RAN: Towards an Elastic Virtualized Architecture for Multiple Distributed Machine Learning Services

Federated learning (FL) is the most popular distributed machine learning technique. However, implementation of FL over modern wireless networks faces key challenges caused by (i) dynamics of the network conditions and (ii) the coexistence of multiple FL services/tasks and other network services in the system, which are not jointly considered in prior works. Motivated by these challenges, we introduce a generic FL paradigm over NextG networks, called dynamic multi-service FL (DMS-FL). We identify three unexplored design considerations in DMS-FL: (i) FL service operator accumulation, (ii) wireless resource fragmentation, and (iii) signal strength fluctuations. We take the first steps towards addressing these design considerations by proposing a novel distributed ML architecture called elastic virtualized FL (EV-FL). EV-FL unleashes the full potential of Open RAN (O-RAN) systems and introduces an elastic resource provisioning methodology to execute FL services. It further constitutes a multi-time-scale FL management system that introduces three dimensions into existing FL architectures: (i) virtualization, (ii) scalability, and (iii) elasticity. Through investigating EV-FL, we reveal a series of open research directions for future work. We finally simulate EV-FL to demonstrate its potential in saving wireless resources and increasing fairness among FL services.Comment: 8 pages, 6 figure

Occurrence of antibiotics in mussels and clams from various FAO areas

Filter feeders, like mussels and clams, are suitable bioindicators of environmental pollution. These shellfish, when destined for human consumption, undergo a depuration step that aims to nullify their pathogenic microorganism load and decrease chemical contamination. Nevertheless, the lack of contamination by drugs may not be guaranteed. Antimicrobials are a class of drugs of particular concern due to the increasing phenomenon of antibiotic resistance. Their use in breeding and aquaculture is a major cause of this. We developed a multiclass method for the HPLC\ue2\u80\u93MS/MS analysis of 29 antimicrobials, validated according to the Commission Decision 2002/657/UE guidelines, and applied it to 50 mussel and 50 clam samples derived from various Food and Agricultural Organisation marine zones. The results obtained, indicate a negligible presence of antibiotics. Just one clam sample showed the presence of oxytetracycline at a concentration slightly higher than the European Union Maximum residue limit set for fish

A Machine Learning framework for Sleeping Cell Detection in a Smart-city IoT Telecommunications Infrastructure

The smooth operation of largely deployed Internet of Things (IoT) applications will depend on, among other things, effective infrastructure failure detection. Access failures in wireless network Base Stations (BSs) produce a phenomenon called "sleeping cells", which can render a cell catatonic without triggering any alarms or provoking immediate effects on cell performance, making them difficult to discover. To detect this kind of failure, we propose a Machine Learning (ML) framework based on the use of Key Performance Indicator (KPI) statistics from the BS under study, as well as those of the neighboring BSs with propensity to have their performance affected by the failure. A simple way to define neighbors is to use adjacency in Voronoi diagrams. In this paper, we propose a much more realistic approach based on the nature of radio-propagation and the way devices choose the BS to which they send access requests. We gather data from large-scale simulators that use real location data for BSs and IoT devices and pose the detection problem as a supervised binary classification problem. We measure the effects on the detection performance by the size of time aggregations of the data, the level of traffic and the parameters of the neighborhood definition. The Extra Trees and Naive Bayes classifiers achieve Receiver Operating Characteristic (ROC) Area Under the Curve (AUC) scores of 0.996 and 0.993, respectively, with False Positive Rate (FPR) under 5 %. The proposed framework holds potential for other pattern recognition tasks in smart-city wireless infrastructures, that would enable the monitoring, prediction and improvement of the Quality of Service (QoS) experienced by IoT applications.Comment: Submitted to the IEEE Access Journa

Evolution of the Anisakis risk management in the European and Italian context

Due to the social and legislative implications, the presence of Anisakis spp. larvae in fishery products has become a concern for both the consumers and the official Control Authorities. The issuance of a large number of provisions, aimed at better managing fish products intended to be consumed raw or almost raw and the associated risks, resulted in a very complicate legal framework. In this work, we analyzed the evolution of the normative through an overview on the local and international legislations, focusing on issues that are of practical interest for Food Business Operators (FBOs) in the fishery chain. In addition, we performed a survey across the Department of Prevention of the Italian Local Health Authorities (LHA) and the main fish markets in Italy to collect the operating procedures and the monitoring plans. Overall, we found many differences, due to the absence of a national reference standard for the management of the Anisakis risk. From this examination, it turns clear that only a participation of all the involved institutions, a strategy of synergistic interventions, as well as a correct training of FBOs, can result in an effective risk management and a proper risk communication, which should overcome states of confusion and unnecessary negative impacts on the economy

Comparing Mobile Laser Scanner and manual measurements for dendrometric variables estimation in a black pine (Pinus nigra Arn.) plantation

The growing demand of ecosystem services provided by forests increased the need for fast and accurate field survey. The recent technological innovations fostered the application of geomatic tools and processes to different fields of the forestry sector. In this study we compared the efficiency and the accuracy of Mobile Laser Scanner (MLS), combined with Simultaneous Localization and Mapping (SLAM) technology, and traditional field survey for the mensuration of main forest dendrometric variables like stem diameter at breast height (DBH), individual tree height (H), crown base height (CBH) and branch-free stem volume (VOL). With ground truth measurements taken from 50 felled trees, we tested the applicability of MLS technology for individual tree parameters esti-mation in a conifer plantation in central Italy. Our results showed no bias of DBH estimates and the corre-sponding RMSE was equal to 10.8% (2.7 cm). H and CBH measured with MLS were underestimated compared to the ground truth (bias of-8.6% for H and-13.3% for CBH). VOL values showed a bias and a RMSE of-4.1% (-0.01 m(3)) and 12.4% (0.04 m3) respectively. Tree height is not perfectly estimated due to laser obstruction by crowns layer, but the acquisition speed of this survey, joined with a suitable accuracy of parameters extraction, suggests sufficient suitability of the method for operational applications in simple forest structures (e.g. one-layered stands)