Definition of Project-Based Learning Models in the Computer Engineering Degree

[EN] The current characteristics, concerns, preferences, and interests of students differ greatly from the previous students¿ generations. Nowadays, students are increasingly demanding active methodologies that facilitate their learning process. To meet the actual students¿ requirements, academic research is focused on the definition of educational mechanisms that promote greater students¿ participation. Among these mechanisms, the project-based learning (PBL) is a model that organizes learning around projects. Projects are student-driven and provide more tangible results what has been considered as a positive aspect to deepen and retain knowledge. The main objective of this paper is to describe all the activities performed to plan, define, design and project an integrated PBL model for students in the last years (3rd and 4th year students) of the Computer Engineering Degree. The PBL model involves the following subjects: (i) Software Engineering; (ii) Project Management; (ii) Business Requirements Analysis and (iv) Business Models and Organisation Functional Areas. The PBL model has twofold perspectives, the first one is more project and software-directed while the second one is more businessoriented. This model seeks to give continuity to the teaching-learning process so that students can appreciate greater coherence, links, and succession of the contents of different subjects. Moreover, the definition of the PBL model will also support the enhancement of the horizontal and vertical transversal coordination among different subjects.This article has been supported by the Vice-rectorate for Digital Resources and Documentation (Vicerrectorado de Recursos Digitales y Documentación) and Vice-Rectorate for Studies, Quality and Accreditation (Vicerrectorado de Estudios, Calidad y Acreditación) under the Call for Learning + Teaching (Convocatoria Aprendizaje + Docencia (A+D 2019)) and Project Code: 1678-A. The authors would like to acknowledge the support of the Institute of Educational Sciences (Instituto de Ciencias de la Educación) of Universitat Politècnica de València, the Evaluation and Monitoring Commission for Educational Innovation and Improvement Projects (Comisión de Evaluación y Seguimiento de Proyectos de Innovación y Mejora Educativa - CESPIME) and Escuela Politécnica Superior de AlcoyEsparza Peidro, J.; Golf Laville, EJ.; Izquierdo-Doménech, JJ.; Tomas Miquel, JV.; Sanchis, R. (2020). Definition of Project-Based Learning Models in the Computer Engineering Degree. EDULEARN Proceedings (Internet). 3966-3972. https://doi.org/10.21125/edulearn.2020.1074S3966397

Application of stochastic programming to reduce uncertainties in quality-based supply planning of slaughterhouses

To match products of different quality with end market preferences under supply uncertainty, it is crucial to integrate product quality information in logistics decision making. We present a case of this integration in a meat processing company that faces uncertainty in delivered livestock quality. We develop a stochastic programming model that exploits historical product quality delivery data to produce slaughterhouse allocation plans with reduced levels of uncertainty in received livestock quality. The allocation plans generated by this model fulfil demand for multiple quality features at separate slaughterhouses under prescribed service levels while minimizing transportation costs. We test the model on real world problem instances generated from a data set provided by an industrial partner. Results show that historical farmer delivery data can be used to reduce uncertainty in quality of animals to be delivered to slaughterhouses

Supply Chain Intelligence

This chapter provides on overall picture of business intelligence (BI) and supply chain analytics (SCA) as a means to support supply chain management (SCM) and decision-making. Based on the literature review, we clarify the needs of BI and performance measurement in the SCM sphere, and discuss its potential to enhance decision-making in strategic, tactical and operational levels. We also make a closer look in to SCA in different areas and functions of SCM. Our findings indicate that the main challenge for harnessing the full potential of SCA is the lack of holistic and integrated BI approaches that originates from the fact that each functional area is using its own IT applications without necessary integration in to the company’s overall BI system. Following this examination, we construct a holistic framework that illustrates how an integrated, managerially planned BI system can be developed. Finally, we discuss the main competency requirements, as well as the challenges still prohibiting the great majority of firms from building smart and comprehensive BI systems for SCM.fi=vertaisarvioitu|en=peerReviewed

Bladder cancer index: cross-cultural adaptation into Spanish and psychometric evaluation

BACKGROUND: The Bladder Cancer Index (BCI) is so far the only instrument applicable across all bladder cancer patients, independent of tumor infiltration or treatment applied. We developed a Spanish version of the BCI, and assessed its acceptability and metric properties. METHODS: For the adaptation into Spanish we used the forward and back-translation method, expert panels, and cognitive debriefing patient interviews. For the assessment of metric properties we used data from 197 bladder cancer patients from a multi-center prospective study. The Spanish BCI and the SF-36 Health Survey were self-administered before and 12 months after treatment. Reliability was estimated by Cronbach's alpha. Construct validity was assessed through the multi-trait multi-method matrix. The magnitude of change was quantified by effect sizes to assess responsiveness. RESULTS: Reliability coefficients ranged 0.75-0.97. The validity analysis confirmed moderate associations between the BCI function and bother subscales for urinary (r = 0.61) and bowel (r = 0.53) domains; conceptual independence among all BCI domains (r ≤ 0.3); and low correlation coefficients with the SF-36 scores, ranging 0.14-0.48. Among patients reporting global improvement at follow-up, pre-post treatment changes were statistically significant for the urinary domain and urinary bother subscale, with effect sizes of 0.38 and 0.53. CONCLUSIONS: The Spanish BCI is well accepted, reliable, valid, responsive, and similar in performance compared to the original instrument. These findings support its use, both in Spanish and international studies, as a valuable and comprehensive tool for assessing quality of life across a wide range of bladder cancer patients

Perioperative fracture-dislocation of the humeral head during a resurfacing hemiarthroplasty

We report a case of perioperative fracture-dislocation of the humeral head produced during the reaming for a resurfacing replacement hemiarthroplasty (RRH) in a 79-year old woman. This is a surgical complication not previously described in the literature for this type of prosthesis design. Resurfacing humeral head implant has been noted as a useful treatment for glenohumeral arthropathies, also in elderly people, with a very low incidence of complications. However, as we report, they are possible

Optimization models for supply chain production planning under fuzziness

[EN] The aim of this chapter is to propose diverse fuzzy mathematical programming models based on the fuzzy set theory for supply chain production planning in a multi-product, multi-plant environment with fuzziness and capacity constraints. The proposed models consider fuzziness in demand and at the aspiration level of total costs. The main contribution of this chapter to the field of fuzzy sets is a practical application of flexible programming approaches (or fuzzy constraints) in linear programming with diverse aggregation schemes to the model originally proposed by McDonald and Karimi (1997)for supply chain production planning.This work has been funded by the Universitat Politècnica de València projects: ‘Material Requirement Planning Fourth Generation (MRPIV)’ (Ref. PAID-05-12) and ‘Quantitative Models for the Design of Socially Responsible Supply Chains under Uncertainty Conditions. Application of Solution Strategies based on Hybrid Metaheuristics’ (PAID-06-12).Mula, J.; Peidro Payá, D.; Poler, R. (2014). Optimization models for supply chain production planning under fuzziness. Studies in Fuzziness and Soft Computing. 313:397-422. https://doi.org/10.1007/978-3-642-53939-8_17S397422313Anupindi, R., Bassok, Y.: Supply contracts with quantity commitments and stochastic demand. Quantitative Models for Supply Chain Management. Kluwer Academic Publishers, Norwell (1999)Bellman, R., Zadeh, L.: Decision making in a fuzzy environment. Manage. Sci. 17(4), 141–164 (1970)CPLEX Optimization Inc. Using the CPLEX callable library (1994)Dubois, D., Fargier, H., Fortemps, P.: Fuzzy scheduling: modelling flexible constraints vs. coping with incomplete knowledge. Eur. J. Oper. Res. 147, 231–252 (2003)Gupta, A., Maranas, C.D.: Managing demand uncertainty in supply chain planning. Comput. Chem. Eng. 27, 1219–1227 (2003)Hahn, C.K., Duplaga, E.A., Kartley, J.L.: Supply-chain synchronization: lessons from Hyundai Motor company. Interfaces 30(4), 32–45 (2000)Hamacher, H., Leberling, H., Zimmermann, H.J.: Sensitivity analysis in fuzzy linear programming. Fuzzy Sets Syst. 1, 269–281 (1978)Itoh, T., Ishii, H., Nanseki, T.: A model of crop planning under uncertainty in agricultural management. Int. J. Prod. Econ. 81–82, 555–558 (2003)Liu, Y.H., Shi, Y.: A fuzzy programming approach for solving a multiple criteria and multiple contraint level linear programming problem. Fuzzy Sets Syst. 65, 117–124 (1994)Luhandjula, M.K.: Compensatory operations in fuzzy linear programming with multiple objectives. Fuzzy Sets Syst. 8, 245–252 (1982)Maximal Software Incorporation. MPL modelling system. Release 4.12, USA (2004)McDonald, C.M., Karimi, I.A.: Planning and scheduling of parallel semicontinuous processes. 1. Production planning. Ind. Eng. Chem. Res. 36, 2691–2700 (1997)Miller, W.A., Leung, L.C., Azhar, T.M., Sargent, S.: Fuzzy production planning model for fresh tomato packing. Int. J. Prod. Econ. 53, 227–238 (1997)Mula, J., Diaz-Madroñero, M., Peidro, D., Vicens, E.: Mathematical programming models for supply chain production and transport planning. Eur. J. Oper. Res. 204, 377–390 (2010a)Mula, J., Peidro, D., Poler, R.: The effectiveness of a fuzzy mathematical programming approach for supply chain production planning with fuzzy demand. Int. J. Prod. Econ. 128, 136–143 (2010b)Mula, J., Poler, R.: Fuzzy material requirement planning. Stud. Fuzziness Soft Comput. 252, 39–57 (2010)Mula, J., Poler, R., García, J.P.: MRP with flexible constraints: a fuzzy mathematical programming approach. Fuzzy Sets Syst. 157, 74–97 (2006a)Mula, J., Poler, R., Garcia, J.P.: Material requirement planning with fuzzy constraints and fuzzy coefficients. Fuzzy Sets Syst. 158, 783–793 (2007a)Mula, J., Poler, R., García, J.P., Lario, F.C.: Models for production planning under uncertainty: a review. Int. J. Prod. Econ. 103, 271–285 (2006b)Mula, J., Poler, R., Garcia-Sabater, J.P.: Fuzzy production planning model for automobile seat assembly. Adv. Soft Comput. 37, 163–171 (2007b)Negoita, C.V., Sularia, M.: On fuzzy programming and tolerances in planning. ECECSR J. 1, 3–15 (1976)Peidro, D., Mula, J., Poler, R., Lario, F.C.: Quantitative models for supply chain planning under uncertainty: a review. Int. J. Adv. Manuf. Technol. 43, 400–420 (2009)Pendharkar, P.C.: A fuzzy linear programming model for production planning in coal mines. Comput. Oper. Res. 24, 1141–1149 (1997)Shi, Y., Liu, Y.H.: Fuzzy potential solutions in multicriteria and multiconstraint level linear programming problems. Fuzzy Sets Syst. 60, 163–179 (1993)Tayur, S., Ganeshan, R., Magazine, M.: Quantitative models for supply chain management. Kluwer, Boston (1999)Werners, B.: An interactive fuzzy programming system. Fuzzy Sets Syst. 23, 131–147 (1987)Zimmermann, H.J.: Description and optimization of fuzzy systems. Int. J. Gen. Syst. 2, 209–215 (1976)Zimmermann, H.J.: Fuzzy programming and linear programming with several objective functions. Fuzzy Sets Syst. 1, 45–55 (1978)Zimmermann, H.J.: Fuzzy Set Theory and its applications, third edition. Kluwer Academic Publishers, Boston (1996)Zimmermann, H.J., Zysno, P.: Latent connectives in human decision making. Fuzzy Sets Syst. 4, 37–51 (1980

Asymptotic statistical analysis for model-based control design strategies

In this paper, we generalize existing fundamental limitations on the accuracy of the estimation of dynamic models. In addition, we study the large sample statistical behavior of different estimation-based controller design strategies. In particular, fundamental limitations on the closed-loop performance using a controller obtained by Virtual Reference Feedback Tuning (VRFT) are studied. We also extend our results to more general estimation-based control design strategies. We present numerical examples to show the application of our results. © 2011 Elsevier Ltd. All rights reserved.This work has been partially supported by the project GVPRE/2008/116 financed by Generalitat Valenciana (Spain). This paper was not presented at any IFAC meeting. This paper was recommended for publication in revised form by Associate Editor Guoxiang Gu under the direction of Editor Torsten Soderstrom.Esparza Peidro, A.; Agüero, JC.; Rojas, CR.; Godoy, BI. (2011). Asymptotic statistical analysis for model-based control design strategies. Automatica. 47(5):1041-1046. https://doi.org/10.1016/j.automatica.2011.01.0581041104647