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.
Mineral and metallurgical processing are crucial within the mineral value chain. These processes involve several stages wherein comminution is arguably the most important due to its high energy consumption, and its impact on subsequent extractive processes. Several geological properties of the orebody impact the efficiency of mineral processing and extractive metallurgy; scholars have therefore proposed to deal with the uncertain ore feed in terms of grades and rock types, incorporating operational modes that represent different plant configurations that provide coordinated system-wide responses. Even though these studies offer insights into how mine planning impacts the ore fed into the plant, the simultaneous optimization of mine plan and metallurgical plant design has been limited by the existing stochastic mine planning algorithms, which have only limited support for detailing operational modes. The present work offers to fill this gap for open-pit mines through a computationally efficient adaptation of a strategic mine planning algorithm. The adaptation incorporates a linear programming representation of the operational modes which forms a Dantzig-Wolfe decomposition, nested within a high-performing stochastic mine planning algorithm based on a variable neighborhood descent metaheuristic. Sample calculations are presented, loosely based on the Mount Isa deposit in Australia, in which a metallurgical plant upgrade is evaluated, showing that the upgraded design significantly decreases the requirement on the mining equipment, without significantly affecting the NPV.
Resumen: En el año 1992 DeLone & McLean (D&M) definieron por medio de un modelo de medida multidimensional, qué es el éxito de un SI y sus correspondientes medidas, clasificándolas en seis categorías interdependientes. Considerando que los pequeños entornos generalmente no cuentan con personal especializado en este tipo de temas, en este trabajo se propone una guía que facilita la aplicación del modelo de D&M para la evaluación de productos de software para pequeños entornos. El principal aporte de esta guía radica en la definición de pasos y en el catálogo de preguntas pre-establecidas para que un pequeño entorno, sin poseer conocimientos acabados en el modelo, pueda rápidamente preparar los instrumentos necesarios para su aplicación. Esta guía fue aplicada en una empresa, demostrando su utilidad para ayudar a los pequeños entornos en la evaluación de los productos de software que dan soporte a sus procesos de negocio.
Abstract: In 1992 DeLone & McLean defined a model of Information SystemsSuccess which includes six interdependent categories. Considering that smallenvironment software developments usually do not have specialized personnel in this type of topic, this paper proposes a guide that facilitates the application of the D&M model for the evaluation of software products. The main contribution of this guideline lies on the definition of steps and on the catalog of pre-established questions which helps small-environment software developments quickly prepare the necessary instruments for its application. This guide was applied in a firm, demonstrating its utility to this type of environments in the evaluation of software products that support their business processes.
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