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, compromising its correct working. In this paper, it is proposed a fuzzy architecture for computing an index which provides a quantitative refined assessment about the quality of the soldered interconnections. This task is performed by reproducing the modus operandi of the human experts during their assessments. The proposed architecture consists of three modules connected in series: a feature extraction block and two fuzzy ones. The presented solution keeps the benefits of a neurofuzzy system previously proposed in literature, like the reduction of equipment and computational costs. Moreover, it implies two further advantages: the influence of the human experts in its design is reduced and its implementation is reasonable. Experimental results confirm such advantages, in fact, the architecture approximates the human assessments reliably.

The paper introduces the issue of the typical defects in PhotoVoltaic (PV) cells and focuses the attention on three specific defects: linear edge shunt, hole and conductive intrusion. These defects are modeled by means of Finite Element Method (FEM) and implemented in Comsol Multiphysics environment in order to analyze the temperature distribution in the whole defected PV cell. All the three typologies of Silicon-based PV cells are considered: mono-crystalline, poly-crystalline and amorphous. Numerical issues (simulation times, degrees of freedom, mesh elements and grid dependence analysis) are reported.

In recent years, the development of photonic crystal fibers has allowed novel opportunities for enhancing optical amplifier characteristics. In this field, accurate numerical modeling is a significant need to predict the device behavior. Conventional approaches perform this task by using methods which could yield solutions characterized by divergent or unstably convergent algorithms. Global optimization methods can be considered as efficient tools to face this problem. In this paper, the application of particle swarm optimization to perform the design and characterization of photonic crystal fiber amplifiers is proposed. The employment of this technique shows different attractive features. In particular, solutions are found quickly and the implementation of the algorithm does not require complicated evolutionary operators. Numerical results show the effectiveness of the approach for both the design and characterization of a fiber amplifier. In fact, if considered as a design tool, the obtained numerical results are in good accordance with respect to the ones yielded by a conventional approach. If considered as a characterization tool, the algorithm performs a forecasting, allowing to determine parameters, such as homogeneous upconversion coefficients, whose computation could present difficulties when it is obtained via direct or indirect measurements.