Automatic assessment of object oriented programming assignments with unit testing in Python and a real case assignment

In this paper, we focus on developing automatic assessment (AA) for a topic that has some difficulties in its practical assessment: object oriented programming (OOP). For evaluating that the OOP principles have been correctly applied to a real application, we use unit testing. In this paper, we focus on prioritizing that the students understand and apply correctly complex OOP principles and that they design properly the classes (including their relationships). In addition, we focus on the Python programming language rather than the typical previous works' focus in this area. Thus, we present a real case study of a practical assignment, in which the students have to implement characters for a video game. This assignment has the particularities and advantages that it is incremental and that it applies all four OOP principles within a single assignment. We also present its solution with the UML class diagram description. Furthermore, we provide unit testing for this case study and give general advice for generalizing the unit tests to other real case scenarios. Finally, we corroborate the effectiveness of our approach with positive student evaluation

Smart and sustainable scheduling of charging events for electric buses

This paper presents a framework for the efficient management of renewable energies to charge a fleet of electric buses (eBuses). Our framework starts with the prediction of clean energy time windows, i.e., periods of time when the production of clean energy exceeds the demand of the country. Then, the optimization phase schedules charging events to reduce the use of non-clean energy to recharge eBuses while passengers are embarking or disembarking. The proposed framework is capable of overcoming the unstable and chaotic nature of wind power generation to operate the fleet without perturbing the quality of service. Our extensive empirical validation with real instances from Ireland suggests that our solutions can significantly reduce non-clean energy consumed on large data setsThis work received funding from the Sustainable Energy Authority of Ireland (SEAI) Research, Development and Demonstration (RDD) 2019 programme under the grant number 19/ RDD/51

Transition to eBuses with minimal timetable disruptions

The implementation of a sustainable and efficient electric transportation network requires addressing multiple concerns such as: limited driving range, battery charging/discharging times and avoiding battery damages. Therefore, the transition to a fully electric bus transportation system involves multiple challenges including timetable design and the charging location problem. In this paper, we address these problems that arise by transitioning from regular diesel buses to electric buses (eBuses)

Assessment of Variable Geometry Orifice Compressor Technology Impact in a New Generation of Compression Ignition Powertrains at Low-End and Transient Operation

[EN] Surge is a phenomenon that limits the operating range of the compressor at low engine speeds and high boost pressure in turbocharged powertrains. This article assesses two prototype turbochargers of variable geometry orifice (VGO) which compensate for the limitation of the boost pressure at low engine speeds. The VGO prototypes modify the inlet compressor section, extending the compressor characteristic map into lower mass flows (surge limit region). The VGO turbochargers analyzed are also both equipped with variable geometry turbine (VGT) technology. The experiments focus on low-end torque operation ranges in steady and transient engine running conditions. The experimental results are used to validate a 1D physical model. From the modelling perspective, a comprehensive study of the VGO-VGT prototypes is assessed. Results reveal the benefits of VGO technology in terms of attaining higher boost pressure, improved compressor efficiency, and overall engine performance at low engine speeds.This research work has been supported by Grant PDC2021-120821-I00 funded by the Spanish Ministerio de Ciencia e Innovacion-Agencia Estatal de Investigacion (MCIN/AEI/10.13039/501100011033), and by the European Union NextGenerationEU/PRTR.Serrano, J.; Climent, H.; Gómez-Vilanova, A.; Darbhamalla, A.; Guilain, S. (2022). Assessment of Variable Geometry Orifice Compressor Technology Impact in a New Generation of Compression Ignition Powertrains at Low-End and Transient Operation. Applied Sciences. 12(24):1-19. https://doi.org/10.3390/app122412869119122

La producción de la muerte y del otro como el mal

Esta ponencia trata sobre la configuración y las transformaciones en el proceso histórico vivido por los ex presos políticos de la última dictadura militar, como grupo violentado por la dictadura militar en San Juan analizando los complejos cambios acaecidos en la correlación de fuerzas y en la condición social de ambos grupos en el interregno de 45 años. La producción de la muerte como objetivo planificado por un sector con poder es una forma concreta del mal. Este era atribuido, como una producción ideológica, por la dictadura a los subversivos. El mal, generalmente abordado como un concepto moral o filosófico aquí es considerado como una categoría sociológica. Para un estudio que se ubica dentro de la historia reciente se ha centralizado en el análisis de la continuidad y trayectoria de un grupo que jugó un papel importante en la Argentina a través de 40 años.Fil: Casas, José. Universidad Nacional de San JuanFil: Carelli, Alejandro. Universidad Nacional de San JuanFil: García, Alicia. Universidad Nacional de San JuanFil: Larreta, Gerardo. Universidad Nacional de San JuanFil: Climent, Andrea. Universidad Nacional de San JuanFil: Aguilera, Celina. Universidad Nacional de San Jua

On the impact of turbocharger thermo-mechanical limitations on new generation gasoline engines

[EN] Among other advances in spark ignited internal combustion engines' field, the variable geometry turbine (VGT) is being analysed to achieve further CO2 reduction objectives. This paper analyses the potential implications of replacing nowadays standard, the waste-gate (WG) technology, with VGT.To do so, after developing a robust and validated model, this work proposes a methodology to optimize the variable valve timing (VVT), at full load working conditions, in a new generation spark ignited (SI) engine, coupled to a VGT prototype. The optimization methodology accounts for the different thermo-mechanical limits of such technology compared to the reference WG turbocharger, particularly in terms of the turbine inlet temperature (T3). Torque differences show a systematic improvement by using a VGT, reaching approximately 22 Nm of improvement and about 17 g/kWh, although the difference in torque is smaller after 3500 rpm due to the more restrictive T3 limit imposed.As well, at partial loads, the same procedure is developed, but targeting the optimization of the engine efficiency. At partial loads, when no exhaust gas recirculation technique is applied, few advantages are identified. However, with exhaust gasses recirculation (EGR) technique, improvements reach 3 g/kWh and permit extending the desired EGR rate towards the lower speeds.Acknowledgements This research has been supported by Grant PID2020-114289RB-I00 funded by MCIN/AEI/10.13039/501100011033. The authors wish to thank Vicente Esteve Ferrer for his invaluable work during the experimental campaignSerrano, J.; Climent, H.; De La Morena, J.; Gómez-Vilanova, A. (2023). On the impact of turbocharger thermo-mechanical limitations on new generation gasoline engines. Applied Thermal Engineering. 222. https://doi.org/10.1016/j.applthermaleng.2022.11993422

La producción de la muerte y del otro como el mal

Esta ponencia trata sobre la configuración y las transformaciones en el proceso histórico vivido por los ex presos políticos de la última dictadura militar, como grupo violentado por la dictadura militar en San Juan analizando los complejos cambios acaecidos en la correlación de fuerzas y en la condición social de ambos grupos en el interregno de 45 años. La producción de la muerte como objetivo planificado por un sector con poder es una forma concreta del mal. Este era atribuido, como una producción ideológica, por la dictadura a los subversivos. El mal, generalmente abordado como un concepto moral o filosófico aquí es considerado como una categoría sociológica. Para un estudio que se ubica dentro de la historia reciente se ha centralizado en el análisis de la continuidad y trayectoria de un grupo que jugó un papel importante en la Argentina a través de 40 años.Fil: Casas, José. Universidad Nacional de San JuanFil: Carelli, Alejandro. Universidad Nacional de San JuanFil: García, Alicia. Universidad Nacional de San JuanFil: Larreta, Gerardo. Universidad Nacional de San JuanFil: Climent, Andrea. Universidad Nacional de San JuanFil: Aguilera, Celina. Universidad Nacional de San Jua

Incorporation of acoustic sensors in the regulation of a mobile robot

This article introduces the incorporation of acoustic sensors for the localization of a mobile robot. The robot is considered as a sound source and its position is located applying a Time Delay of Arrival (TDOA) method. Since the accuracy of this method varies with the microphone array, a navigation acoustic map that indicates the location errors is built. This map also provides the robot with navigation trajectories point-to-point and the control is capable to drive the robot through these trajectories to a desired configuration. The proposed localization method is thoroughly tested using both a 900 Hz square signal and the natural sound of the robot, which is driven near the desired point with an average error of 0:067 m.This is an Accepted Manuscript of an article published by Taylor & Francis in Advanced Robotics on 01/01/2019, available online: http://www.tandfonline.com/10.1080/01691864.2019.1573703.”Peer ReviewedPostprint (author's final draft

Pruebas unitarias para evaluar automáticamente la programación de clases en python

[EN] The Automatic Assessment (AA) of tasks presents several advantages, such as: its application to a large number of students (due to the very short time that it requires compared to manual evaluations), automatic and immediate feedback to the students and lack of subjectivity . In this paper we explain how to design unit tests to evaluate how the Object Oriented Programming (OOP) classes of the assignment have been programmed. In this paper, we focus on the Python programming language (rather than using Java as other works of literature). In addition, we present a real case of practical laboratory assignment. We also present their solution and the corresponding unit tests. Finally, we prove the effectiveness of the unit tests by verifying that the results obtained are the same as the evaluation carried out by visual inspection of the students’ code. In addition, we also received positive feedback from students on the work presented in this article.[ES] La Evaluación Automática (EA) de tareas presenta varias ventajas, tales como: su aplicación a un gran número de estudiantes (debido al tiempo tan reducido que requiere en comparación con las evaluaciones manuales), valoración automática e inmediata para los estudiantes y falta de subjetividad.En este trabajo explicamos como diseñar pruebas unitarias para evaluar como han sido programadas las clases de tareas de Programación Orientada a Objetos (POO). En este trabajo, nos enfocamos en el lenguaje de programación Python (en vez de utilizar Java tal y como lo hacen los otros trabajos de la literatura). Además, presentamos un caso real de un trabajo práctico de laboratorio. También presentamos su solución y las correspondientes pruebas unitarias.Finalmente, corroboramos la efectividad de los tests unitarios comprobando que los resultados obtenidos son los mismos que la evaluación realizada por inspección visual del código de los estudiantes. Además, también recibimos valoraciones positivas de los alumnos del trabajo presentado en este artículo.Climent Aunes, L.; Arbelaez Rodriguez, A. (2023). Pruebas unitarias para evaluar automáticamente la programación de clases en python. Editorial Universitat Politècnica de València. 398-408. https://doi.org/10.4995/INRED2023.2023.1659639840

A hybrid metaheuristic with learning for a real supply chain scheduling problem

In recent decades, research on supply chain management (SCM) has enabled companies to improve their environmental, social, and economic performance. This paper presents an industrial application of logistics that can be classified as an inventory-route problem. The problem consists of assigning orders to the available warehouses. The orders are composed of items that must be loaded within a week. The warehouses provide an inventory of the number of items available for each day of the week, so the objective is to minimize the total transportation costs and the costs of producing extra stock to satisfy the weekly demand. To solve this problem a formal mathematical model is proposed. Then a hybrid approach that involves two metaheuristics: a greedy randomized adaptive search procedure (GRASP) and a genetic algorithm (GA) is proposed. Additionally, a meta-learning tuning method is incorporated into our hybridized approach, which yields better results but with a longer computation time. Thus, the trade-off of using it is analyzed. An extensive evaluation was carried out over realistic instances provided by an industrial partner. The proposed technique was evaluated and compared with several complete and incomplete solvers from the state of the art (CP Optimizer, Yuck, OR-Tools, etc.). The results showed that our hybrid metaheuristic outperformed the behavior of these well-known solvers, mainly in large-scale instances (2000 orders per week). This hybrid algorithm provides the company with a powerful tool to solve its supply chain management problem, delivering significant economic benefits every week.The authors gratefully acknowledge the financial support of the European Social Fund (Investing In Your Future), the Spanish Ministry of Science (project PID2021-125919NB-I00), and valgrAI - Valencian Graduate School and Research Network of Artificial Intelligence and the Generalitat Valenciana, Spain, and co-funded by the European Union. The authors also thank the industrial partner Logifruit for its support in the problem specification and the permission to generate randomized data for evaluating the proposed algorithm