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El presente trabajo busca comparar los contextos socio-políticos en los cuales se han desarrollado los movimientos estudiantiles universitarios de Brasil y Venezuela. Se hará un resumen histórico del desarrollo político de ambos países durante los siglos XX y XXI, revisando sus ciclos democráticos y dictatoriales cronológicamente, posteriormente se presentará un breve resumen de los momentos y acciones más importantes de los movimientos estudiantiles universitarios de ambos países y sus liderazgos, para finalmente establecer diferencias y semejanzas entre los dos movimientos. La categoría elegida para el estudio es parte de la propuesta de Maria da Glória Gohn para el estudio de los movimientos sociales, esquema conceptual que permite una delimitación y aproximación adecuadas a los movimientos de interés.

Evacuation route planning is a fundamental task for building engineering projects. Safety regulations are established so that all occupants are driven on time out of a building to a secure place when faced with an emergency situation. As an example, Spanish building code requires the planning of evacuation routes on large and, usually, public buildings. Engineers often plan these routes on single building projects, repeatedly assigning clusters of rooms to each emergency exit in a trial-and-error process. But problems may arise for a building complex where distribution and use changes make visual analysis cumbersome and sometimes unfeasible. This problem could be solved by using well-known spatial analysis techniques, implemented as a specialized software able to partially emulate engineer reasoning. In this paper we propose and test an easily reproducible methodology that makes use of free and open source software components for solving a case study. We ran a complete test on a building floor at the University of Alicante (Spain). This institution offers a web service (WFS) that allows retrieval of 2D geometries from any building within its campus. We demonstrate how geospatial technologies and computational geometry algorithms can be used for automating the creation and optimization of evacuation routes. In our case study, the engineers’ task is to verify that the load capacity of each emergency exit does not exceed the standards specified by Spain’s current regulations. Using Dijkstra’s algorithm, we obtain the shortest paths from every room to the most appropriate emergency exit. Once these paths are calculated, engineers can run simulations and validate, based on path statistics, different cluster configurations. Techniques and tools applied in this research would be helpful in the design and risk management phases of any complex building project.

This paper examines the problem of agricultural land abandonment through knowledge of driving factors. First, we reach out a review of the concept of abandonment in order to define the negative and positive aspects of this process in the landscape. Then we focus on a real case study in the Marina Baja region (SE Spain). Finally, we propose, from a theoretical perspective, the use of a methodology to define the most important variables for studying the abandonment processes in this region. First of all, we performed various analyses using Geographical Information Systems (GIS) to create a geodatabase which stores the main factors generally associated with abandonment. The variables considered can be grouped into three groups: environmental (such as climate, soils or relief), socio-economic (such as demographic, accessibility or technology) and those related to cultural practices in the crop (such as irrigation or rain-fed stone walls). Considering over a hundred variables we need to answer two questions: (1) which of the variables are really driving factors in the abandonment process of an agricultural plot? and (2) how important is each of them alone or in combination with others? The authors advocate the use of GIS for the feature creation or management and Data Mining techniques to perform the feature selection. Specifically, we propose the use of a concrete metric, aci (Attribute Correlation Index), to answer the questions raised above.