GEOSTATISTICAL METHODS TO MEASURE THE NATURE 2000 HABITAT INSULARIZATION IN ITALY

It is interesting to notice how Nature 2000 is described as an instrument of “widespread ecological network throughout the EU territories”, insisting in a definitional imprecision that has been dragging on for more than twenty years, and that was often, also authoritatively, criticized by many. Undoubtedly, many of these elements constitute the focal point of local ecological networks for species conservation importance, but their functionality depends on equally undoubtedly by the presence of ecologically permeable matrices that enable the biotic flows dynamics. The Italian Regions are the subjects of this study, as an expression of homogeneous forms of territorial government and as a reference on the administrative level for the implementation of Community policies for Nature 2000 network. The method followed in the work refers to an evaluate spatial fragmentation conditions methodology and the SCIs are the evaluated patches, which have a high dispersion on the national territory. This research has been conducted to show how the central issue of habitat and species conservation is still currently the fragmentation provoked by mobility infrastructures and urban planning Keyword

Google earth engine as multi-sensor open-source tool for supporting the preservation of archaeological areas: The case study of flood and fire mapping in metaponto, italy

In recent years, the impact of Climate change, anthropogenic and natural hazards (such as earthquakes, landslides, floods, tsunamis, fires) has dramatically increased and adversely affected modern and past human buildings including outstanding cultural properties and UNESCO heritage sites. Research about protection/monitoring of cultural heritage is crucial to preserve our cultural properties and (with them also) our history and identity. This paper is focused on the use of the open-source Google Earth Engine tool herein used to analyze flood and fire events which affected the area of Metaponto (southern Italy), near the homonymous Greek-Roman archaeological site. The use of the Google Earth Engine has allowed the supervised and unsupervised classification of areas affected by flooding (2013–2020) and fire (2017) in the past years, obtaining remarkable results and useful information for setting up strategies to mitigate damage and support the preservation of areas and landscape rich in cultural and natural heritage

Ten years of feasibility pump, and counting

The Feasibility Pump (fp) is probably the best-known primal heuristic for mixed-integer programming. The original work by Fischetti et al. (Math Program 104(1):91\u2013104, 2005), which introduced the heuristic for 0\u20131 mixed-integer linear programs, has been succeeded by more than twenty follow-up publications which improve the performance of the fp and extend it to other problem classes. Year 2015 was the tenth anniversary of the first fp publication. The present paper provides an overview of the diverse Feasibility Pump literature that has been presented over the last decade

Strengthening a regional green infrastructure through improved multifunctionality and connectedness: Policy suggestions from Sardinia, Italy

A wide body of research in the latest years has studied either green infrastructures as providers of multiple ecosystem services, especially at the urban level, or ecological corridors and the issue of connectivity between landscape patches in the face of growing fragmentation. However, not many studies have analyzed how the two concepts can be combined to ground evidence-based policy and planning recommendations. In this study, a methodological approach for such combination is proposed: after mapping a regional green infrastructure building upon the assessment of multiple ecosystem services, and a network of ecological corridors through resistance to movement of species, the two spatial layouts are combined so as to analyze correlations between the potential provision of ecosystem services and the resistance to movement. The methodology is applied in the case of the island of Sardinia, whose self-containment makes it possible to discard potential effects from surrounding areas, hence facilitating the implementation of the model. The outcomes of the regression model point out to three ecosystem services as the most important factors that should be targeted by appropriate spatial policies, if connectivity is to be increased: regulation of micro and local climate, forestry productivity, and cultural identity and heritage values

SmartFog: Training the Fog for the energy-saving analytics of Smart-Meter data

In this paper, we characterize the main building blocks and numerically verify the classification accuracy and energy performance of SmartFog, a distributed and virtualized networked Fog technological platform for the support for Stacked Denoising Auto-Encoder (SDAE)-based anomaly detection in data flows generated by Smart-Meters (SMs). In SmartFog, the various layers of an SDAE are pretrained at different Fog nodes, in order to distribute the overall computational efforts and, then, save energy. For this purpose, a new Adaptive Elitist Genetic Algorithm (AEGA) is “ad hoc” designed to find the optimized allocation of the SDAE layers to the Fog nodes. Interestingly, the proposed AEGA implements a (novel) mechanism that adaptively tunes the exploration and exploitation capabilities of the AEGA, in order to quickly escape the attraction basins of local minima of the underlying energy objective function and, then, speed up the convergence towards global minima. As a matter of fact, the main distinguishing feature of the resulting SmartFog paradigm is that it accomplishes the joint integration on a distributed Fog computing platform of the anomaly detection functionality and the minimization of the resulting energy consumption. The reported numerical tests support the effectiveness of the designed technological platform and point out that the attained performance improvements over some state-of-the-art competing solutions are around 5%, 68% and 30% in terms of detection accuracy, execution time and energy consumption, respectively

Nonlinear multiscale viscosity methods and time integration schemes for solving compressible Euler equations

Este trabalho apresenta duas formulações do método de elementos finitos, utilizando estabilização multiescala, para resolver o sistema de equações de Euler compressíveis bidimensionais em variáveis conservativas. O espaço submalha é definido através de funções polinomiais que se anulam na fronteira dos elementos, conhecidas como funções bolha, permitindo o uso de um complemento de Schur local para definir o problema das escalas resolvidas. Esse procedimento resulta em uma metodologia numérica que permite variações temporais das escalas não resolvidas. As formulações propostas neste trabalho são baseadas em resíduo e consideram viscosidade artificial agindo em todas as escalas de discretização. Na primeira formulação um operador não linear é adicionado sobre todas as escalas, já na segunda formulação diferentes operadores não lineares são incluídos sobre as escalas macro e micro. A eficiência das novas formulações são avaliadas através de estudos numéricos, comparando-as com outras formulações, tais como os métodos SUPG combinado com o operador de captura de choque YZBeta e CAU. Outra contribuição que este trabalho apresenta diz respeito ao avanço no tempo, uma vez que métodos baseados em densidade sofrem com efeitos indesejados em escoamento com baixa velocidade, o que inclui convergência lenta e perda de acurácia. Devido a esse fenômeno, a técnica de precondicionamento local é aplicada às equações no caso contínuo. Uma alternativa para resolver esta deficiência consiste em utilizar esquemas de avanço no tempo com propriedade de decaimento como L-estabilidade. Com esse intuito é proposto um esquema preditor-corretor baseado em Backward Differentiation Formulas (BDF) cuja predição é realizada através de extrapolação

IoT-Based Applications in Healthcare Devices

The last decade has witnessed extensive research in the field of healthcare services and their technological upgradation. To be more specific, the Internet of Things (IoT) has shown potential application in connecting various medical devices, sensors, and healthcare professionals to provide quality medical services in a remote location. This has improved patient safety, reduced healthcare costs, enhanced the accessibility of healthcare services, and increased operational efficiency in the healthcare industry. The current study gives an up-to-date summary of the potential healthcare applications of IoT- (HIoT-) based technologies. Herein, the advancement of the application of the HIoT has been reported from the perspective of enabling technologies, healthcare services, and applications in solving various healthcare issues. Moreover, potential challenges and issues in the HIoT system are also discussed. In sum, the current study provides a comprehensive source of information regarding the different fields of application of HIoT intending to help future researchers, who have the interest to work and make advancements in the field to gain insight into the topic

RustOnt: An Ontology to Explain Weather Favorable Conditions of the Coffee Rust

Crop disease management in smart agriculture involves applying and using new technologies to reduce the impact of diseases on the quality of products. Coffee rust is a disease that factors such as poor agronomic management activities and climate conditions may favor. Therefore, it is crucial to identify the relationships between these factors and this disease to learn how to face its consequences and build intelligent systems to provide appropriate management or help farmers and experts make decisions accordingly. Nevertheless, there are no studies in the literature that propose ontologies to model these factors and coffee rust. This paper presents a new ontology called RustOnt to help experts more accurately model data, expressions, and samples related to coffee rust and apply it whilst taking into account the geographical location where the ontology is adopted. Consequently, this ontology is crucial for coffee rust monitoring and management by means of smart agriculture systems. RustOnt was successfully evaluated considering quality criteria such as clarity, consistency, modularity, and competence against a set of initial requirements for which it was built.project "System based on knowledge engineering for the agroecological management of coffee rust", grant 823-Formation of high-level human capital for the regions-Cauc