Uso integrato di sistemi di video monitoraggio e di misura delle prestazioni per migliorare il livello di sicurezza sul lavoro

Una delle tecnologie spesso presenti nelle aziende è rappresentata dai sistemi di videosorveglianza. Se da un lato l’efficacia di tali sistemi ai fini della sicurezza antintrusione è ampiamente riconosciuta, le potenzialità di un loro utilizzo per scopi di sicurezza sul lavoro non risultano ancora indagate. Il presente articolo illustra un progetto di ricerca applicata sviluppato dal gruppo di Impianti Industriali della Facoltà di Ingegneria dell’Università degli Studi di Brescia volto ad analizzare la potenziale utilità dell’utilizzo di sistemi di videosorveglianza per monitorare efficacemente le attività lavorative al fine di misurare, e quindi incrementare, il livello di salute e sicurezza sul lavoro. Nell’ambito del progetto, un sistema di video monitoraggio affiancato da un sistema di misura delle performance è stato implementato in un’azienda manifatturiera. La sperimentazione, resa possibile da un accordo tra parte datoriale e sindacale, ha consentito l’identificazione di interventi prioritari da attuare in azienda per il miglioramento del livello di sicurezza. Infatti, grazie all’analisi delle videoriprese è stato possibile individuare sia condizioni a rischio, che comportamenti a rischio o sicuri, connaturati con la specifica tipologia di attività dell’azienda. Le informazioni ed i dati così raccolti hanno consentito la quantificazione degli indicatori definiti dal sistema di misura delle prestazioni. Dall’analisi dell’andamento degli indicatori, si è evidenziato un aumento dei comportamenti sicuri durante il periodo di sperimentazione. Tale andamento può essere interpretato come conseguenza di breve periodo dell’effetto deterrenza legato all’installazione delle videocamere nei reparti produttivi. Una valutazione dell’efficacia di lungo periodo del sistema in termini di miglioramento del livello di sicurezza sul lavoro sarà possibile solamente a valle di ulteriori sperimentazioni. ------ Video surveillance systems represent one of the types of technology often available in companies. Even though the effectiveness of such systems for security reasons is well recognized, their potential for occupational safety reasons have not been investigated yet. This paper describes a research project, developed by the Industrial Plant group of the Engineering Faculty of the University of Brescia. The aim of the project is to analyse the potential of the use of video surveillance systems with the objective of effectively monitoring the working activity in order to measure, and therefore increase, the level of health and safety at work. Within the project, a video surveillance system coupled with a performance measurement system has been implemented in a manufacturing company. Through the experimentation of the system, that was possible because of an agreement between employer and unions, the priority interventions to implement in order to improve the safety level in the company have been identified. In fact, by means of the analysis of the video records, it was possible to identify both conditions at risk, and safe or at risk behaviours specific for the company. The gathered data made it possible to quantify the indicators included in the performance measurement system. A trend analysis of the indicators showed that the amount of safe behaviours increased during the experimentation period. This trend could be considered as a consequence in the short term of the deterrence effect connected to video cameras installation in the plant. An assessment of the long term effectiveness of the system in terms of safety level improvement will be possible only after further experimentations

A Collaborative and Distributed Learning-Based Solution to Autonomously Plan Computer Networks

The high programmability provided by Software Defined Networking (SDN) paradigm facilitated the integration of Machine Learning (ML) methods to design a new family of network management schemes. Among them, we can cite self-driving networks, where ML is used to analyze data and define strategies that are then translated into network configurations by the SDN controllers, making the networks autonomous and capable of auto-scaling decisions based on the network’s needs. Despite their attractiveness, the centralized design of the majority of proposed solutions cannot keep up with the increasing size of the network. To this end, this paper investigates the use of a multiagent reinforcement learning (MARL) model for auto-scaling decisions in an SDN environment. In particular, we study two possible alternatives for distributing operations: a collaborative one, where controllers share the same observations, and an individual one, where controllers make decisions according to their own logic and share only some basic information, such as the network topology. After an experimental campaign performed both on Mininet and GENI, results showed that both approaches can guarantee high throughput while minimizing the set of active resources

Kinematics and Kinetics of Bulgarian-Bag-Overloaded Sprints in Young Athletes

Background: Eective sprinting requires large acceleration capabilities. To accelerate, large amount of force must be produced and applied eectively. The use of dierent implements such as sleds and vests can increase the amount of force produced and alter sprinting eectiveness. We propose the use of increasing overload via the Bulgarian Bag (BB) as a means to modify athletes\u2019 sprint and acutely increase force and power production. Methods: 24 young athletes performed three sprints over 20 m in three dierent conditions: unloaded (BW) and loaded with BB weighing 2.5% (BB2.5) and 5% (BB5) of the athlete\u2019s body mass. Sprint times at 2.5, 5, 10, 15, and 20 m were acquired and used to compute the force\u2013velocity relationship for the sprints. Maximal velocity (V0), peak force (F0), peak power (PP), and decrease in ratio of force (DRF) were computed. Results: the additional load caused a decrease in sprint times (p < 0.05) and V0 (p = 0.028), conversely no dierences were found for F0 (p = 0.21), PP (p = 0.50), and DRF (p = 0.83). Conclusions: Based on those findings, BB can be an alternative method to eectively overload sprint training toward improving sprinting performance

Impact of leaf removal after berry set on fruit composition and bunch rot in 'Sauvignon blanc'

Leaf removal is a viticultural practice applied to improve cluster microclimate and grape composition. This practice can reduce the incidence of bunch rot but could also promote the degradation of berry methoxypyrazines, key components for the aromatic profile of 'Sauvignon blanc' wines. The influence of cluster-zone leaf removal, applied after berry set, was evaluated on 'Sauvignon blanc' grapevines grown in the Isonzo DOC region (Italy). In 2010 and 2011, yield components and fruit chemical composition were recorded from vines in which the five basal leaves of each single shoot were manually removed at the groat-sized phenological stage, and compared to untreated vines. Our results indicated that leaf removal did not influence yield or fruit composition at harvest, but significantly decreased the incidence and severity of Botrytis bunch rot, while reducing the severity of sunburn damage to the fruit. Increased sunlight cluster exposure decreased 2-methoxy-3-isobutylpyrazine (IBMP) and 3-isopropyl-2-methoxypyrazine (IPMP) concentrations in early stages of berry development, whereas at harvest no significant differences between treatments (defoliated and non-defoliated) were observed. We conclude that leaf removal performed after berry set is a pivotal viticultural management practice to cope with harvest bunch rot complex without negatively affecting fruit composition at harvest

Clear cell odontogenic carcinoma: a case report and literature review

Abstract Clear cell odontogenic carcinoma (CCOC) is a rare odontogenic tumor of the jaw with a particular histology and a deceptive behavior. The clinical presentation may be misleading, that is why the contribution of incisional biopsy, molecular biology, immunohistochemistry and cytogenetics is essential in the diagnostic process. This review article aims to discuss its various aspects, summarizing the currently published studies of CCOC to enhance the diagnosis and to present a case report of a 41-year-old man that presented to the Department of Maxillofacial Surgery at Gemelli University Hospital in Rome, Italy

“Scelte per il futuro” terzo incontro mondiale sui paesaggi terrazzati: Italia, 6-15 ottobre 2016

Il Terzo Incontro Mondiale è stato preparato per diversi anni dalla Sezione italiana dell’ITLA con il supporto del Comitato internazionale. Sono stati selezionati e visitati i luoghi che avrebbero ospitato i diversi incontri tematiche, individuate le persone e le organizzazioni di riferimento locale che in seguito sarebbero state documentate in brevi videoclip. I protagonisti locali (amministrazioni locali, associazioni culturali, sezioni del Club Alpino Italiano, presidi Slowfood, produttori di vino e cooperative …) hanno preparato con grande impegno le loro visite sul luogo organizzate per presentare al meglio sia la situazione attuale che i loro progetti di futuro. Il comitato organizzativo ha dato a ciascun sito uno tema specifico che sarebbe stato sviluppato durante il viaggio di studio. In ogni sito i partecipanti hanno presentato la loro esperienza sull’argomento specifico condividendola con gli attori locali. Questa tipologia organizzativa ha permesso il coinvolgimento attivo dei partecipanti e ha favorito la preparazione di un contributo concreto al dialogo e alla ricerca di opzioni future per i paesaggi terrazzati

Cortical Complexity Estimation Using Fractal Dimension: A Systematic Review of the Literature on Clinical and Nonclinical Samples

Fractal geometry has recently been proposed as a useful tool for characterizing the complexity of the brain cortex, which is likely to derive from the recurrence of sulci–gyri convolution patterns. The index used to describe the cortical complexity is called fractal dimensional (FD) and was employed by different research exploring the neurobiological correlates of distinct pathological and nonpathological conditions. This review aims to describe the literature on the application of this index, summarize the heterogeneities between studies and inform future research on this topic. Sixty-two studies were included in the systematic review. The main research lines concern neurodevelopment, aging and the neurobiology of specific psychiatric and neurological disorders. Overall, the included papers indicate that cortical complexity is likely to reduce during aging and in various pathological processes affecting the brain. Nevertheless, the high heterogeneity between studies strongly prevents the possibility of drawing conclusions. Further research considering this index besides other morphological values is needed to better clarify the role of FD in characterizing the cortical structure

AI Lifecycle Zero-Touch Orchestration within the Edge-to-Cloud Continuum for Industry 5.0

The advancements in human-centered artificial intelligence (HCAI) systems for Industry 5.0 is a new phase of industrialization that places the worker at the center of the production process and uses new technologies to increase prosperity beyond jobs and growth. HCAI presents new objectives that were unreachable by either humans or machines alone, but this also comes with a new set of challenges. Our proposed method accomplishes this through the knowlEdge architecture, which enables human operators to implement AI solutions using a zero-touch framework. It relies on containerized AI model training and execution, supported by a robust data pipeline and rounded off with human feedback and evaluation interfaces. The result is a platform built from a number of components, spanning all major areas of the AI lifecycle. We outline both the architectural concepts and implementation guidelines and explain how they advance HCAI systems and Industry 5.0. In this article, we address the problems we encountered while implementing the ideas within the edge-to-cloud continuum. Further improvements to our approach may enhance the use of AI in Industry 5.0 and strengthen trust in AI systems