This paper describes the process of generating a predictive model of students’ academic performance in different engineering subjects at Universidad Católica del Norte (UCN). It aims to analyze the importance of variables influencing the final average grade of the UCN students in projects related to different subjects, focusing on the dimensions resulting from the Belbin test. The main objective of this work is to provide evidence of the real impact of the Belbin test outcomes on the final performance of a team of students, using as a metric of variable importance the one provided by a Random Forest model, supplied by the scikit‐learn library. As a result, the final classifier presented an accuracy of 80%, and one of the most influential variables according to this model was Covered Roles 2, which represents the number of roles covered in each group. Future research lines are proposed to validate these outcomes, mostly concerned with the acquisition of more data across several future semesters.

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Schemes to write the flow equations in discreet form, solution solvers, pre and post data processing utilities provided by OpenFoam libraries, are used to build a finite volume executable for simulating a low speed, turbulent and rate controlled diffusive CH 4-Air combustion. Unsteady Favre's averaged turbulent conservation equations (total mass, momentum, energy and species mass fractions), are used to describe the combustion gas dynamics, and to handle turbulence a modified k-ε model is applied. Several global kinetic mechanisms, one step, two and four steps have been considered to describe the oxidation process of CH 4 in a free jet type flame. The interaction between chemistry and turbulence, is modeled according to the partially stirred reactor (PaSR) concept. To improve convergence and accuracy in solving low speed fluid dynamic equations, a pressure implicit with splitting of operators (PISO) technique extended to cover high temperature flows, is utilized. The exponential dependence of the chemical kinetics from temperature, makes stiffs the ODE's needed to determine source average values with which the species conservation equations are solved. To deal with the stiffness issue, OpenFoam provides numerical schemes that guaranties the stability of the computation. Comparisons between results of numerical simulations and experimental data obtained with the benchmark known as flame "D", are presented.

Sonification is the science of communication of data and events to users through sounds. Auditory icons, earcons, and speech are the common auditory display schemes utilized in sonification, or more specifically in the use of audio to convey information. Once the captured data are perceived, their meanings, and more importantly, intentions can be interpreted more easily and thus can be employed as a complement to visualization techniques. Through auditory perception it is possible to convey information

Sonification is the utilization of sounds to convey information about data or events. There are two types of emotions associated with sounds: (1) “perceived” emotions, in which listeners recognize the emotions expressed by the sound, and (2) “induced” emotions, in which listeners feel emotions induced by the sound. Although listeners may widely agree on the perceived emotion for a given sound, they often do not agree about the induced emotion of a given sound, so it is difficult to model induced emotions. This paper describes the development of several machine and deep learning models that predict the perceived and induced emotions associated with certain sounds, and it analyzes and compares the accuracy of those predictions. The results revealed that models built for predicting perceived emotions are more accurate than ones built for predicting induced emotions. However, the gap in predictive power between such models can be narrowed substantially through the optimization of the machine and deep learning models. This research has several applications in automated configurations of hardware devices and their integration with software components in the context of the Internet of Things, for which security is of utmost importance.

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and many others. These have gained a national mass media audience, whereas many other smaller scale shootings are known in local communities.