Classification of ductile cast iron specimens: A machine learning approach

In this paper an automatic procedure based on a machine learning approach is proposed to classify ductile cast iron specimens according to the American Society for Testing and Materials guidelines. The mechanical properties of a specimen are strongly influenced by the peculiar morphology of their graphite elements and useful characteristics, the features, are extracted from the specimens’ images; these characteristics examine the shape, the distribution and the size of the graphite particle in the specimen, the nodularity and the nodule count. The principal components analysis are used to provide a more efficient representation of these data. Support vector machines are trained to obtain a classification of the data by yielding sequential binary classification steps. Numerical analysis is performed on a significant number of images providing robust results, also in presence of dust, scratches and measurement noise

Large deflection of a non-linear, elastic, asymmetric Ludwick cantilever beam subjected to horizontal force, vertical force and bending torque at the free end

The investigated cantilever beam is characterized by a constant rectangular cross-section and is subjected to a concentrated constant vertical load, to a concentrated constant horizontal load and to a concentrated constant bending torque at the free end. The same beam is made by an elastic non-linear asymmetric Ludwick type material with different behavior in tension and compression. Namely the constitutive law of the proposed material is characterized by two different elastic moduli and two different strain exponential coefficients. The aim of this study is to describe the deformation of the beam neutral surface and particularly the horizontal and vertical displacements of the free end cross-section. The analysis of large deflection is based on the Euler-Bernoulli bending beam theory, for which cross-sections, after the deformation, remain plain and perpendicular to the neutral surface; furthermore their shape and area do not change. On the stress viewpoint, the shear stress effect and the axial force effect are considered negligible in comparison with the bending effect. The mechanical model deduced from the identified hypotheses includes two kind of non-linearity: the first due to the material and the latter due to large deformations. The mathematical problem associated with the mechanical model, i.e. to compute the bending deformations, consists in solving a non-linear algebraic system and a non-liner second order ordinary differential equation. Thus a numerical algorithm is developed and some examples of specific results are shown in this paper. © Springer Science+Business Media Dordrecht 2014

Pde based inpainting algorithms: performance evaluation of the Cahn-Hillard model

Image inpainting consists in restoring a missing or a damaged part of an image on the basis of the signal information in the pixels sur- rounding the missing domain. To this aim a suitable image model is needed to represent the signal features to be reproduced within the inpainting domain, also depending on the size of the missing area. With no claim of completeness, in this paper the main streamline of the development of the PDE based models is retraced. Then, the Cahn-Hillard model for binary images is analyzed in detail and its performances are evaluated on some numerical experiments

High-resolution SAR images for fire susceptibility estimation in urban forestry

We present an adaptive system for the automatic assessment of both physical and anthropic fire impact factors on periurban forestries. The aim is to provide an integrated methodology exploiting a complex data structure built upon a multi resolution grid gathering historical land exploitation and meteorological data, records of human habits together with suitably segmented and interpreted high resolution X-SAR images, and several other information sources. The contribution of the model and its novelty rely mainly on the definition of a learning schema lifting different factors and aspects of fire causes, including physical, social and behavioural ones, to the design of a fire susceptibility map, of a specific urban forestry. The outcome is an integrated geospatial database providing an infrastructure that merges cartography, heterogeneous data and complex analysis, in so establishing a digital environment where users and tools are interactively connected in an efficient and flexible way

Finite volume and finite element schemes for the euler equations in cylindrical and spherical coordinates

A numerical scheme is presented for the solution of the compressible Euler equations over unstructured grids in cylindrical and spherical coordinates. The proposed scheme is based on a mixed finite volume / finite element approach. Numerical simulations are presented for the explosion problem in two spatial dimensions in cylindrical and spherical coordinates, and the numerical results are compared with the one-dimensional simulation for cylindrically and spherically symmetric explosions

Analgesic effectiveness and tolerability of oral oxycodone/naloxone and pregabalin in patients with lung cancer and neuropathic pain. An observational analysis

INTRODUCTION: Cancer-related pain has a severe negative impact on quality of life. Combination analgesic therapy with oxycodone and pregabalin is effective for treating neuropathic cancer pain. We investigated the efficacy and tolerability of a dose-escalation combination therapy with prolonged-release oxycodone/naloxone (OXN-PR) and pregabalin in patients with non-small-cell lung cancer and severe neuropathic pain. METHODS: This was a 4-week, open-label, observational study. Patients were treated with OXN-PR and pregabalin. Average pain intensity ([API] measured on a 0-10 numerical rating scale) and neuropathic pain (Douleur Neuropathique 4) were assessed at study entry and at follow-up visits. The primary endpoint was response to treatment, defined as a reduction of API at T28 ≥30% from baseline. Secondary endpoints included other efficacy measures, as well as patient satisfaction and quality of life (Brief Pain Inventory Short Form), Hospital Anxiety and Depression Scale, and Symptom Distress Scale; bowel function was also assessed. RESULTS: A total of 56 patients were enrolled. API at baseline was 8.0±0.9, and decreased after 4 weeks by 48% (4.2±1.9; P<0.0001 vs baseline); 46 (82.1%) patients responded to treatment. Significant improvements were also reported in number/severity of breakthrough cancer pain episodes (P=0.001), Brief Pain Inventory Short Form (P=0.0002), Symptom Distress Scale (P<0.0001), Hospital Anxiety and Depression Scale depression (P=0.0006) and anxiety (P<0.0001) subscales, and bowel function (P=0.0003). At study end, 37 (66.0%) patients were satisfied/very satisfied with the new analgesic treatment. Combination therapy had a good safety profile. CONCLUSION: OXN-PR and pregabalin were safe and highly effective in a real-world setting of severe neuropathic cancer pain, with a high rate of satisfaction, without interference on bowel function

Graphite nodules features identifications and damaging micromechanims in ductile irons

Ductile irons mechanical properties are strongly influenced by the metal matrix microstructure and on the graphite elements morphology. Depending on the chemical composition, the manufacturing process and the heat treatments, these graphite elements can be characterized by different shape, size and distribution. These geometrical features are usually evaluated by the experts visual inspection, and some commercial softwares are also available to assist this activity. In this work, an automatic procedure based on an image segmentation technique is applied: this procedure is validated not only considering spheroidal graphite elements, but also considering other morphologies (e.g. lamellae)