The dropout rate of engineering students is a concerning problem at the present time in many countries, resulting in difficulties to follow the demand of professionals in certain technological sectors as well as an associated negative economic impact. This study identifies a number of factors affecting the motivation degree of current electrical and computer engineering students, as well as the main reasons behind the dropout. A survey was completed by 624 students belonging to 8 different Spanish universities, rating the factors that could influence them to abandon their studies and those affecting their motivation to continue studying. Non-parametric analyses were performed in order to test the association of motivation as well as self-reported likelihood of dropping out with several variables. According to the research results, 23 of the 40 analyzed factors are correlated with the degree of motivation and 14 factors are correlated with the self-reported probability of dropping out. About 46% of the students declared to have thought about dropping out at some point in the past. Difficulty, followed by bad academic performance and negative relationships with professors are the main reasons for dropping out given by the students. Lack of vocation and distance to their home address were less frequent reasons.

Contribution: This article explores the factors favoring the enrollment in engineering studies in Spain, analyzing gender differences. Background: Understanding the motivation of choosing engineering studies is very important in order to strengthen this choice in future promotions in Spain, considering that it is well below the average of the European Union at the present time. Research Questions: What are the main factors that influence students to choose engineering studies? Are there any noticeable differences between those affecting male and female students? Methodology: Data were collected from a survey completed by 624 students and an exploratory study was performed extracting five components. Independent sample $T$ -tests were used to determine significant differences between the answers of males and females. Findings: The factors found in the exploratory analysis were “Interest and development,” “Career advice and previous contact,” “Outcome expectations,” “Social influences” and “Not preferred option.” Significant differences between the answers given by males and females were also found. The outcome of this study is important for the development of new interventions aimed to increase interest, enrollment, and retention of engineering students, especially among females.

We present a new approach for the analysis and design of radome structures. It makes use of extended domain macro-basis functions obtained from the characteristic basis function method in order to represent the current distribution over the radome. This involves computational advantages due to the reduction in the number of unknowns compared to conventional approaches. This approach involves dividing the scenario into two domains, antenna and radome, and calculating the influence between them using a technique that iteratively corrects the error of the currents on each domain. This technique can be used to analyze arbitrary-shaped radome antennas including several material layers with different thicknesses and dielectric properties that can embed frequency selective surfaces on any interface. Several test cases are presented for the validation of the proposed technique.

An efficient approach for the generation of sparse preconditioners, tailored for the application of macrobasis function methods, is described in this letter. The preconditioner is highly scalable and generated by the computing groups of rows that share a common sparsity pattern, calculated by using a distance threshold between geometrical blocks that controls the amount of data to be considered. This approach is suitable for the analysis of very large and realistic problems, as shown in some test cases included. Due to the clustering nature of this technique, the preconditioners can be generated in a substantially lower amount of time than that required by conventional approaches.

A technique for the reduction of the CPU time in the solution of scattering problems using the characteristic basis function method (CBFM) is presented. It is suitable to analyze electrically very large cases in which an iterative solution process cannot be avoided, even considering the reduction in the size of the matrix achieved by the CBFM. This technique is based on the definition of a new set of high-level functions that improves the convergence properties of the problem under analysis. The test cases show that the approach provides accurate results for canonical and complex bodies.