Giuseppe Acciani

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The defect detection on manufactures is extremely important in the optimization of industrial processes; particularly, the visual inspection plays a fundamental role. The visual inspection is often carried out by a human expert. However, new technology features have made this inspection unreliable. For this reason, many researchers have been engaged to(More)
Environmental data sets are characterized by a huge amount of heterogeneous data from external fields. As the number of measured points grows, a strategy is needed to select and efficiently analyze the useful information from the whole data set. One efficient way of obtaining the validation-compression of data sets is the adoption of a restricted set of(More)
Recently, surface mount technology is extensively used in the production of printed circuit boards due to the high level of miniaturization and to the increase of density in the electronic device integration. In such production process several defects could occur on the final electronic components, compromising its correct working. In this paper a(More)
In recent years, the requirement of compact devices caused an increasing use of Surface Mount Technology. This technology guarantees the reduction of the size of electronic packages by exploiting solder joint interconnection technology. Nevertheless, parameter variations can occur during the deposition and printing of the soldering paste on a board,(More)
The aim of this paper is to model and simulate a cantilever beam as energy harvester to expose to wind vibrations. A mathematical model describes the behavior of cantilever beam and the electromechanical coupling, using piezoelectric constitutive equations. An experimental setup of a fixed configuration (dimensions, materials, boundaries and shape) is(More)
We describe an algorithm to build a graphical model—more precisely: a join tree representation of a Markov network— for a steady state analog circuit. This model can be used to do probabilistic diagnosis based on manufacturer supplied information about nominal values of electrical components and their tolerances as well as measurements made on the circuit.(More)
We study learning vector quantization methods to adapt the size of (hyper-)spherical clusters to better fit a given data set, especially in the context of non-normalized activations. The basic idea of our approach is to compute a desired radius from the data points that are assigned to a cluster and then to adapt the current radius of the cluster in the(More)