Motores térmicos de vapor, gas y de combustión interna a través de PBL (Project Based Learning)

Nivel educativo: Grado. Duración (en horas): De 31 a 40 horas

Using the system dynamics paradigm in teaching and learning technological university subjets

2nd International Conference on Education and New Learning Technologies

Iraupen luzeko irakasleriaren garapenaren inpaktu-mailak: kontzepzioetan, hezkuntza hurbilketan eta kultura instituzionalean

[EUS]Unibertsitateko irakasleriaren garapenaren(IG) kontzeptu konprentsibotik abiatuta, doktorego tesi honek iraupen luzeko IG programen inpaktua du aztergai, bai maila indibidualean (kontzepzio eta hurbilketan) eta baita maila organizazional zein instituzionalean ere. Azterketa hau burutzeko metodologia aktiboen (arazoetan, proiektuetan eta kasuetan oinarritutako ikaskuntza) ERAGIN programaren lehendabiziko promozioa hartuko da kasu gisa. Iraupen luzeko estrategiaren (350 ordu) bidez eta ko-mentoria taldeen funtzionamenduan oinarrituz, ikerlan enpirikoak IG-ak irakasleriaren ikas-irakaskuntza kontzepzioetan eta hurbilketan izandako inpaktuaz ageriko ebidentziak ematen ditu, baina baita ikas-irakaskuntzaren inguruan ikertzeko (scholarship of teaching and learning) eta irakaskuntza eremuetan liderra izateko gaitasunaz ere. Honako alderdiok aldaketa organizazionalean murgiltzen gaituzte eta curriculum hibridoaren pausokako gauzapenaren alde lan egiten dute.

Learning and management skills: the internationalization of Grupo Arcor. Analysis from a process-based approach

This paper analyzes the path of the international expansion of Grupo Arcor, an Argentine multinational company specializing in confectionery. The objective is to entify corporate strategies and business learning that led this Latin American firm to establish itself as one of the leading manufacturers in confectionery industry ,particularly in the 21st Century. The analysis is primarily qualitative in order to identify the economic dimension as a determinant in the internationalization process; a processbased approach from the Uppsala Model is used for this. However, the study is also complemented with a regression analysis to test if the firm was driven to expand internationally by the expectations on the degree of globalization of the industry and the accumulation of experience in foreign markets, and if the company was influenced by psychic distance in choosing the location of its investment; given the influence of these variables in Grupo Arcor business strategies. Our findings suggest that Grupo Arcor, was able to become global due to strategies such as vertical integration, diversification of products and geographical markets (based on psychic distance) and indeed some strategies were consequence of the globalization of the sector and the accumulation of experience in foreign markets.

Efficient learning of decomposable models with a bounded clique size

The learning of probability distributions from data is a ubiquitous problem in the fields of Statistics and Artificial Intelligence. During the last decades several learning algorithms have been proposed to learn probability distributions based on decomposable models due to their advantageous theoretical properties. Some of these algorithms can be used to search for a maximum likelihood decomposable model with a given maximum clique size, k, which controls the complexity of the model. Unfortunately, the problem of learning a maximum likelihood decomposable model given a maximum clique size is NP-hard for k > 2. In this work, we propose a family of algorithms which approximates this problem with a computational complexity of O(k · n^2 log n) in the worst case, where n is the number of implied random variables. The structures of the decomposable models that solve the maximum likelihood problem are called maximal k-order decomposable graphs. Our proposals, called fractal trees, construct a sequence of maximal i-order decomposable graphs, for i = 2, ..., k, in k − 1 steps. At each step, the algorithms follow a divide-and-conquer strategy based on the particular features of this type of structures. Additionally, we propose a prune-and-graft procedure which transforms a maximal k-order decomposable graph into another one, increasing its likelihood. We have implemented two particular fractal tree algorithms called parallel fractal tree and sequential fractal tree. These algorithms can be considered a natural extension of Chow and Liu’s algorithm, from k = 2 to arbitrary values of k. Both algorithms have been compared against other efficient approaches in artificial and real domains, and they have shown a competitive behavior to deal with the maximum likelihood problem. Due to their low computational complexity they are especially recommended to deal with high dimensional domains.

The Computer Input/Output Subsystem Education in an undergraduate introductory course: a Multiperspective Study

240 p.