Jornadas de Trabajo sobre Historia Reciente (7 : 2014 : La Plata). Actas

Tabla de contenidos: Los alemanes y la Shoah en Colombia, un ejercicio de Historia Oral / Lorena Cardona González. Sobre la categoría de "trauma histórico" para pensar la memoria social / Maximiliano Alberto Garbarino. El estudio de la historia reciente y la memoria colectiva / Ayelén Colosimo. Memoria y espacio biográfico en el peronismo / María Belén Boetto. Esbozos para una epistemología de la historia reciente / Florencia Levín. El reeslabonamiento de la resistencia / Florencia Espinosa. Fotos de la DIPBA en el Museo de Arte y Memoria / Florencia Larralde Armas. Carnaval / María Daniela Alegrucci. A favor de la disidencia / Cristian Secul Giusti. Políticas de Memoria en la post dictadura / Tamara Salinas Rivas. Memorias en disputa / María Delicia Zurita. Memoria y conmemoración / Renato Dinamarca Opazo. Malvinas como relato escolar / Manuela Belinche Montequin. Repensando actos escolares y efemérides / Sofía Breccia, María de los Angeles Gregorio. Paseo de la Memoria de Berazategui / Juan Manuel Facciolo, Mariana Edith Troncoso. Enseñar historia argentina reciente / Yésica Billán. Enseñar Historia Reciente / Rodrigo Edgar Saguas. La Historia Reciente Latinoamericana en las aulas / Mariana Ponisio. Un estado de la cuestión acerca del "Industricidio" en (de) Tucumán y su impacto en el mundo del trabajo rural azucarero entre los años 1966 y 1970 / Pedro García Posse. Proletarización y militancia fabril del PRT - La Verdad (1968 - 1972) / Martín Mangiantini. Elementos para la discusión sobre la formación de una vanguardia obrera revolucionaria en la transición histórica argentina (1969-1976) / Walter Koppmann. Para una historia reciente de la UOCRA La Plata / Rafael Farace. Migrantes limítrofes y su inserción en el mercado laboral del sector de la construcción / María Eleonora Paoletti. "Queremos autonomía y no tiranía" / J. Sebastián Califa. Las disputas en la autonomía universitaria en la UBA entre 1966-1973 / Guadalupe Seia. Las repercusiones de la "Masacre de Trelew" en Bahía Blanca y Punta Alta Dominella,Virginia. La Revista Siguiendo La Huella del Movimiento Rural de ACA (1958-1972) / Leonardo Hernán Fernández. Configuraciones del Movimiento Cromañón / Laura Codaro. "Lo que hicimos desde las bases, lo podíamos hacer desde arriba" / Fernanda Tocho. Un período breve en un pequeño lugar / Luciana Mingrone. Infancia y revolución en el PRT-ERP / Mariela Peller. ¿Intelectuales para la contrainsurgencia? / Alberto Bozza. Los intelectuales liberal-conservadores argentinos ante el ocaso del 'Proceso' y la transición democrática / Martín Vicente. La recepción cristiana de Paulo Freire en Argentina (1968-1974) / Federico Brugaletta. Doctrina de la Seguridad Nacional y representaciones de la figura del 'subversivo' en "Las muñecas que hacen ¡pum!", de Gerardo Sofovich (1979) / Eliana Laura Ferradás Abalo. Arte y militancia / Débora Ermosi. "Que todos los chicos se metan, opinen, intervengan" / María Lucía Abbattista. Violencia y represión en el humor gráfico de Chaupinela y HUM (1974-1980) / Mara Burkart. "No hay revolución sin canciones" / Jimena Alonso. "El cumpleaños de Juan Angel", un punto de quiebre en la vida y obra de Mario Benedetti / Manuel Martínez Ruesta. La Palabra Armada / Mariela Stavale. Reforma curricular, intelectuales y perfiles docentes en la Escuela de Visitadoras de Higiene Social y Enfermería de la UNLP entre 1960 y 1969 / Néstor Arrúa. La formación de docentes universitarios durante la última dictadura cívico-militar / Mónica L. Paso. La Universidad Nacional de Córdoba y la "formación de las almas" durante la dictadura de 1976 / Marta Philp. El proceso de normalización universitaria en la Universidad Nacional del Sur / Rocío Laura Zanetto. La batalla de Ensenada / Marina Illanes. Complicidad civil y represión hacia los trabajadores durante la última dictadura militar argentina / Marina Florencia Lascano. Prisión política y destierro en la Argentina dictatorial / Silvina Jensen, Ma Montero.

Implementación de una secuencia didáctica en la enseñanza de la lectura y escritura en contextos de estudio en la formación docente inicial

Fil: Sánchez, María de los Milagros. Universidad Nacional de La Plata. Facultad de Humanidades y Ciencias de la Educación; Argentina.

Las condiciones de estudio como variable pedagógica de relaciones entre neurobiología y aprendizaje

Fil: Bacigalupe, María de los Angeles. Universidad Nacional de La Plata. Facultad de Humanidades y Ciencias de la Educación; Argentina.

Grid Global Behavior Prediction

Complexity has always been one of the most important issues in distributed computing. From the first clusters to grid and now cloud computing, dealing correctly and efficiently with system complexity is the key to taking technology a step further. In this sense, global behavior modeling is an innovative methodology aimed at understanding the grid behavior. The main objective of this methodology is to synthesize the grid's vast, heterogeneous nature into a simple but powerful behavior model, represented in the form of a single, abstract entity, with a global state. Global behavior modeling has proved to be very useful in effectively managing grid complexity but, in many cases, deeper knowledge is needed. It generates a descriptive model that could be greatly improved if extended not only to explain behavior, but also to predict it. In this paper we present a prediction methodology whose objective is to define the techniques needed to create global behavior prediction models for grid systems. This global behavior prediction can benefit grid management, specially in areas such as fault tolerance or job scheduling. The paper presents experimental results obtained in real scenarios in order to validate this approach.

Parallel and Distributed Data Management. Introduction

The manipulation and handling of an ever increasing volume of data by current data-intensive applications require novel techniques for e?cient data management. Despite recent advances in every aspect of data management (storage, access, querying, analysis, mining), future applications are expected to scale to even higher degrees, not only in terms of volumes of data handled but also in terms of users and resources, often making use of multiple, pre-existing autonomous, distributed or heterogeneous resources.

A Description Framework and Event-Driven Architecture for the Semantic Web and Semantic Grid

In this introductory chapter we put in context and give a brief outline of the work that we thoroughly present in the rest of the dissertation. We consider this work divided in two main parts. The first part is the Firenze Framework, a knowledge level description framework rich enough to express the semantics required for describing both semantic Web services and semantic Grid services. We start by defining what the Semantic Grid is and its relation with the Semantic Web; and the possibility of their convergence since both initiatives have become mainly service-oriented. We also introduce the main motivators of the creation of this framework, one is to provide a valid description framework that works at knowledge level; the other to provide a description framework that takes into account the characteristics of Grid services in order to be able to describe them properly. The other part of the dissertation is devoted to Vega, an event-driven architecture that, by means of proposed knowledge level description framework, is able to achieve high scale provisioning of knowledge-intensive services. In this introductory chapter we portrait the anatomy of a generic event-driven architecture, and we briefly enumerate their main characteristics, which are the reason that make them our choice.

Generación y Gestión Optimizadas de la Base de Datos de un Visual para su Implementación en un Simulador de Formación

Los Sistemas de Información Geográfica están desarrollados para gestionar grandes volúmenes de datos, y disponen de numerosas funcionalidades orientadas a la captura, almacenamiento, edición, organización, procesado, análisis, o a la representación de información geográficamente referenciada. Por otro lado, los simuladores industriales para entrenamiento en tareas de conducción son aplicaciones en tiempo real que necesitan de un entorno virtual, ya sea geoespecífico, geogenérico, o combinación de ambos tipos, sobre el cual se ejecutarán los programas propios de la simulación. Este entorno, en última instancia, constituye un lugar geográfico, con sus características específicas geométricas, de aspecto, funcionales, topológicas, etc. Al conjunto de elementos que permiten la creación del entorno virtual de simulación dentro del cual se puede mover el usuario del simulador se denomina habitualmente Base de Datos del Visual (BDV). La idea principal del trabajo que se desarrolla aborda un tema del máximo interés en el campo de los simuladores industriales de formación, como es el problema que presenta el análisis, la estructuración, y la descripción de los entornos virtuales a emplear en los grandes simuladores de conducción. En este artículo se propone una metodología de trabajo en la que se aprovechan las capacidades y ventajas de los Sistemas de Información Geográfica para organizar, optimizar y gestionar la base de datos visual del simulador, y para mejorar la calidad y el rendimiento del simulador en general. ABSTRACT Geographic Information Systems are developed to handle enormous volumes of data and are equipped with numerous functionalities intended to capture, store, edit, organise, process and analyse or represent the geographically referenced information. On the other hand, industrial simulators for driver training are real-time applications that require a virtual environment, either geospecific, geogeneric or a combination of the two, over which the simulation programs will be run. In the final instance, this environment constitutes a geographic location with its specific characteristics of geometry, appearance, functionality, topography, etc. The set of elements that enables the virtual simulation environment to be created and in which the simulator user can move, is usually called the Visual Database (VDB). The main idea behind the work being developed approaches a topic that is of major interest in the field of industrial training simulators, which is the problem of analysing, structuring and describing the virtual environments to be used in large driving simulators. This paper sets out a methodology that uses the capabilities and benefits of Geographic Information Systems for organising, optimising and managing the visual Database of the simulator and for generally enhancing the quality and performance of the simulator.

Modelos de análisis econométrico espacial aplicados al desarrollo económico

Los modelos de desarrollo regional, rural y urbano arrancaron en la década de los 90 en Estados Unidos, modelando los factores relacionados con la economía que suministran información y conocimiento acerca de cómo los parámetros geográficos y otros externos influencian la economía regional. El desarrollo regional y en particular el rural han seguido diferentes caminos en Europa y España, adoptando como modelo los programas estructurales de la UE ligados a la PAC. El Programa para el Desarrollo Rural Sostenible, recientemente lanzado por el Gobierno de España (2010) no profundiza en los modelos económicos de esta economía y sus causas. Este estudio pretende encontrar pautas de comportamiento de las variables de la economía regional-rural, y como el efecto de distribución geográfica de la población condiciona la actividad económica. Para este propósito, y utilizando datos espaciales y económicos de las regiones, se implementaran modelos espaciales que permitan evaluar el comportamiento económico, y verificar hipótesis de trabajo sobre la geografía y la economía del territorio. Se utilizarán modelos de análisis espacial como el análisis exploratorio espacial y los modelos econométricos de ecuaciones simultáneas, y dentro de estas los modelos ampliamente utilizados en estudios regionales de Carlino-Mills- Boarnet. ABSTRACT The regional development models for rural and urban areas started in USA in the ´90s, modeling the economy and the factors involved to understand and collect the knowledge of how the external parameters influenced the regional economy. Regional development and in particular rural development has followed different paths in Europe and Spain, adopting structural programs defined in the EU Agriculture Common Policy. The program for Sustainable Rural Development recently implemented in Spain (2010) is short sighted considering the effects of the regional economy. This study endeavors to underline models of behavior for the rural and regional economy variables, and how the regional distribution of population conditions the economic activities. For that purpose using current spatial regional economic data, this study will implement spatial economic models to evaluate the behavior of the regional economy, including the evaluation of working hypothesis about geography and economy in the territory. The approach will use data analysis models, like exploratory spatial data analysis, and spatial econometric models, and in particular for its wide acceptance in regional analysis, the Carlino-Mills-Boarnet equations model.

Prototipo de aparcamiento prefabricado

El objeto del proyecto es el estudio, preparación y redacción, de acuerdo con lo exigido al respecto por la Legislación y Normativa vigente, de los documentos necesarios para definir geométrica y constructivamente las obras de ejecución de un aparcamiento sobre rasante en la zona de Las Tablas.

Enhanced Failure Detection Mechanism in MapReduce

The popularity of MapReduce programming model has increased interest in the research community for its improvement. Among the other directions, the point of fault tolerance, concretely the failure detection issue seems to be a crucial one, but that until now has not reached its satisfying level. Motivated by this, I decided to devote my main research during this period into having a prototype system architecture of MapReduce framework with a new failure detection service, containing both analytical (theoretical) and implementation part. I am confident that this work should lead the way for further contributions in detecting failures to any NoSQL App frameworks, and cloud storage systems in general.

An autonomic framework for enhancing the quality of data grid services

Data grid services have been used to deal with the increasing needs of applications in terms of data volume and throughput. The large scale, heterogeneity and dynamism of grid environments often make management and tuning of these data services very complex. Furthermore, current high-performance I/O approaches are characterized by their high complexity and specific features that usually require specialized administrator skills. Autonomic computing can help manage this complexity. The present paper describes an autonomic subsystem intended to provide self-management features aimed at efficiently reducing the I/O problem in a grid environment, thereby enhancing the quality of service (QoS) of data access and storage services in the grid. Our proposal takes into account that data produced in an I/O system is not usually immediately required. Therefore, performance improvements are related not only to current but also to any future I/O access, as the actual data access usually occurs later on. Nevertheless, the exact time of the next I/O operations is unknown. Thus, our approach proposes a long-term prediction designed to forecast the future workload of grid components. This enables the autonomic subsystem to determine the optimal data placement to improve both current and future I/O operations.

Riding out of the storm: How to deal with the complexity of grid and cloud management

Over the last decade, Grid computing paved the way for a new level of large scale distributed systems. This infrastructure made it possible to securely and reliably take advantage of widely separated computational resources that are part of several different organizations. Resources can be incorporated to the Grid, building a theoretical virtual supercomputer. In time, cloud computing emerged as a new type of large scale distributed system, inheriting and expanding the expertise and knowledge that have been obtained so far. Some of the main characteristics of Grids naturally evolved into clouds, others were modified and adapted and others were simply discarded or postponed. Regardless of these technical specifics, both Grids and clouds together can be considered as one of the most important advances in large scale distributed computing of the past ten years; however, this step in distributed computing has came along with a completely new level of complexity. Grid and cloud management mechanisms play a key role, and correct analysis and understanding of the system behavior are needed. Large scale distributed systems must be able to self-manage, incorporating autonomic features capable of controlling and optimizing all resources and services. Traditional distributed computing management mechanisms analyze each resource separately and adjust specific parameters of each one of them. When trying to adapt the same procedures to Grid and cloud computing, the vast complexity of these systems can make this task extremely complicated. But large scale distributed systems complexity could only be a matter of perspective. It could be possible to understand the Grid or cloud behavior as a single entity, instead of a set of resources. This abstraction could provide a different understanding of the system, describing large scale behavior and global events that probably would not be detected analyzing each resource separately. In this work we define a theoretical framework that combines both ideas, multiple resources and single entity, to develop large scale distributed systems management techniques aimed at system performance optimization, increased dependability and Quality of Service (QoS). The resulting synergy could be the key 350 J. Montes et al. to address the most important difficulties of Grid and cloud management.

Harmony: Towards automated self-adaptive consistency in cloud storage

In just a few years cloud computing has become a very popular paradigm and a business success story, with storage being one of the key features. To achieve high data availability, cloud storage services rely on replication. In this context, one major challenge is data consistency. In contrast to traditional approaches that are mostly based on strong consistency, many cloud storage services opt for weaker consistency models in order to achieve better availability and performance. This comes at the cost of a high probability of stale data being read, as the replicas involved in the reads may not always have the most recent write. In this paper, we propose a novel approach, named Harmony, which adaptively tunes the consistency level at run-time according to the application requirements. The key idea behind Harmony is an intelligent estimation model of stale reads, allowing to elastically scale up or down the number of replicas involved in read operations to maintain a low (possibly zero) tolerable fraction of stale reads. As a result, Harmony can meet the desired consistency of the applications while achieving good performance. We have implemented Harmony and performed extensive evaluations with the Cassandra cloud storage on Grid?5000 testbed and on Amazon EC2. The results show that Harmony can achieve good performance without exceeding the tolerated number of stale reads. For instance, in contrast to the static eventual consistency used in Cassandra, Harmony reduces the stale data being read by almost 80% while adding only minimal latency. Meanwhile, it improves the throughput of the system by 45% while maintaining the desired consistency requirements of the applications when compared to the strong consistency model in Cassandra.

GMonE: a complete approach to cloud monitoring

The inherent complexity of modern cloud infrastructures has created the need for innovative monitoring approaches, as state-of-the-art solutions used for other large-scale environments do not address specific cloud features. Although cloud monitoring is nowadays an active research field, a comprehensive study covering all its aspects has not been presented yet. This paper provides a deep insight into cloud monitoring. It proposes a unified cloud monitoring taxonomy, based on which it defines a layered cloud monitoring architecture. To illustrate it, we have implemented GMonE, a general-purpose cloud monitoring tool which covers all aspects of cloud monitoring by specifically addressing the needs of modern cloud infrastructures. Furthermore, we have evaluated the performance, scalability and overhead of GMonE with Yahoo Cloud Serving Benchmark (YCSB), by using the OpenNebula cloud middleware on the Grid’5000 experimental testbed. The results of this evaluation demonstrate the benefits of our approach, surpassing the monitoring performance and capabilities of cloud monitoring alternatives such as those present in state-of-the-art systems such as Amazon EC2 and OpenNebula.

Felipe II y el virreinato valenciano (1567-1578) : la apuesta por la eficacia gubernativa

Bibliografía: p. 305-311