Acceso abierto a las publicaciones científicas : definición, recursos, copyright e impacto

Publicado en: El Profesional de la Información 15(4): pp. 255-66 (2005)El movimiento a favor del acceso abierto a las publicaciones científicas (Open access) cada vez tiene más adeptos y apoyo, tanto institucional como de los miembros de la comunidad científica, y también son numerosas las manifestaciones e iniciativas en torno al mismo. Este artículo analiza el significado de Open access o Acceso abierto a las publicaciones científicas a través de internet de acuerdo con las declaraciones de Budapest, Bethesda y Berlín. Se revisan algunos aspectos relacionados con el impacto de las revistas OA y las implicaciones de la cesión de derechos de copyright en el acceso abierto. Por último se evalúan las perspectivas de futuro del acceso en abierto desde el punto de vista de las políticas.Peer reviewe

Robust Flows over Time: Models and Complexity Results

We study dynamic network flows with uncertain input data under a robust optimization perspective. In the dynamic maximum flow problem, the goal is to maximize the flow reaching the sink within a given time horizon $T$, while flow requires a certain travel time to traverse an edge. In our setting, we account for uncertain travel times of flow. We investigate maximum flows over time under the assumption that at most $\Gamma$ travel times may be prolonged simultaneously due to delay. We develop and study a mathematical model for this problem. As the dynamic robust flow problem generalizes the static version, it is NP-hard to compute an optimal flow. However, our dynamic version is considerably more complex than the static version. We show that it is NP-hard to verify feasibility of a given candidate solution. Furthermore, we investigate temporally repeated flows and show that in contrast to the non-robust case (that is, without uncertainties) they no longer provide optimal solutions for the robust problem, but rather yield a worst case optimality gap of at least $T$. We finally show that the optimality gap is at most $O(\eta k \log T)$, where $\eta$ and $k$ are newly introduced instance characteristics and provide a matching lower bound instance with optimality gap $\Omega(\log T)$ and $\eta = k = 1$. The results obtained in this paper yield a first step towards understanding robust dynamic flow problems with uncertain travel times

Pre-processing for Triangulation of Probabilistic Networks

The currently most efficient algorithm for inference with a probabilistic network builds upon a triangulation of a network's graph. In this paper, we show that pre-processing can help in finding good triangulations forprobabilistic networks, that is, triangulations with a minimal maximum clique size. We provide a set of rules for stepwise reducing a graph, without losing optimality. This reduction allows us to solve the triangulation problem on a smaller graph. From the smaller graph's triangulation, a triangulation of the original graph is obtained by reversing the reduction steps. Our experimental results show that the graphs of some well-known real-life probabilistic networks can be triangulated optimally just by preprocessing; for other networks, huge reductions in their graph's size are obtained.Comment: Appears in Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence (UAI2001

Проблемы сохранности личных данных сотрудников в организации

Каждый человек обладает личной информацией, который в праве, распоряжаться только он сам. К персональным данным человека относится не только рост и вес, но и данные о его рождении, место проживания, образование, серия и номер паспорта, которые в современном обществе от нас требуют в каждой организации. А на сколько, защищены наши персональные данные, при передаче их иному лицу? Кто несет ответственность за безопасное хранение данной информации

Recoverable Robust Knapsacks: the Discrete Scenario Case

Admission control problems have been studied extensively in the past. In a typical setting, resources like bandwidth have to be distributed to the different customers according to their demands maximizing the profit of the company. Yet, in real-world applications those demands are deviating and in order to satisfy their service requirements often a robust approach is chosen wasting benefits for the company. Our model overcomes this problem by allowing a limited recovery of a previously fixed assignment as soon as the data are known by violating at most k service promises and serving up to l new customers. Applying this approaches to the call admission problem on a single link of a telecommunication network leads to a recoverable robust version of the knapsack problem