370 research outputs found

    The K-Server Dual and Loose Competitiveness for Paging

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    This paper has two results. The first is based on the surprising observation that the well-known ``least-recently-used'' paging algorithm and the ``balance'' algorithm for weighted caching are linear-programming primal-dual algorithms. This observation leads to a strategy (called ``Greedy-Dual'') that generalizes them both and has an optimal performance guarantee for weighted caching. For the second result, the paper presents empirical studies of paging algorithms, documenting that in practice, on ``typical'' cache sizes and sequences, the performance of paging strategies are much better than their worst-case analyses in the standard model suggest. The paper then presents theoretical results that support and explain this. For example: on any input sequence, with almost all cache sizes, either the performance guarantee of least-recently-used is O(log k) or the fault rate (in an absolute sense) is insignificant. Both of these results are strengthened and generalized in``On-line File Caching'' (1998).Comment: conference version: "On-Line Caching as Cache Size Varies", SODA (1991

    La metacognición y el mejoramiento de la enseñanza de química universitaria

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    En este trabajo, que es parte de una investigación más extensa, sobre mejoramiento de la enseñanza de química universitaria, se presentan algunos resultados obtenidos luego de aplicar una nueva propuesta de enseñanza, destinada a la comprensión y resolución de problemas sobre el tema «Soluciones». Con el objeto de facilitar el aprendizaje significativo, la propuesta de trabajo incluye el uso de las denominadas herramientas metacognitivas que permitan aplicar metodologías conducentes al logro de dichos aprendizajes por parte de los estudiantes. Luego de aplicar las mencionadas herramientas, se procedió a realizar la evaluación de los estudiantes participantes para obtener datos sobre los logros alcanzados y sus aprendizajes. El análisis de los resultados muestra que el uso del nuevo enfoque instruccional ayuda a los estudiantes en sus procesos de aprendizaje, en la medida que se vayan haciendo conscientes de los mecanismos que se utilizan para obtener aprendizaje significativo.This work, which is part of a more extensive research project on the improvement of Chemistry teaching at university level, presents the results obtained by applying an innovative teaching methodology. This methodology was designed with the objective of helping students to better understand and solve problems regarding the topic "Solutions". In order to facilitate learning, the proposed methodology includes the use of metacognitive tools (concept maps, Gowin's Vee and clinical interviews), which allows the students to apply significant learning methodologies. After applying these tools, we evaluated the students in order to measure their achievements and their learning. The analysis of the results shows that the use of this new instructional approach helps the students in their learning process because they become aware of the mechanism they use to achieve significant learning

    Information Gathering in Ad-Hoc Radio Networks with Tree Topology

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    We study the problem of information gathering in ad-hoc radio networks without collision detection, focussing on the case when the network forms a tree, with edges directed towards the root. Initially, each node has a piece of information that we refer to as a rumor. Our goal is to design protocols that deliver all rumors to the root of the tree as quickly as possible. The protocol must complete this task within its allotted time even though the actual tree topology is unknown when the computation starts. In the deterministic case, assuming that the nodes are labeled with small integers, we give an O(n)-time protocol that uses unbounded messages, and an O(n log n)-time protocol using bounded messages, where any message can include only one rumor. We also consider fire-and-forward protocols, in which a node can only transmit its own rumor or the rumor received in the previous step. We give a deterministic fire-and- forward protocol with running time O(n^1.5), and we show that it is asymptotically optimal. We then study randomized algorithms where the nodes are not labelled. In this model, we give an O(n log n)-time protocol and we prove that this bound is asymptotically optimal

    Approximating Weighted Duo-Preservation in Comparative Genomics

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    Motivated by comparative genomics, Chen et al. [9] introduced the Maximum Duo-preservation String Mapping (MDSM) problem in which we are given two strings s1s_1 and s2s_2 from the same alphabet and the goal is to find a mapping π\pi between them so as to maximize the number of duos preserved. A duo is any two consecutive characters in a string and it is preserved in the mapping if its two consecutive characters in s1s_1 are mapped to same two consecutive characters in s2s_2. The MDSM problem is known to be NP-hard and there are approximation algorithms for this problem [3, 5, 13], but all of them consider only the "unweighted" version of the problem in the sense that a duo from s1s_1 is preserved by mapping to any same duo in s2s_2 regardless of their positions in the respective strings. However, it is well-desired in comparative genomics to find mappings that consider preserving duos that are "closer" to each other under some distance measure [19]. In this paper, we introduce a generalized version of the problem, called the Maximum-Weight Duo-preservation String Mapping (MWDSM) problem that captures both duos-preservation and duos-distance measures in the sense that mapping a duo from s1s_1 to each preserved duo in s2s_2 has a weight, indicating the "closeness" of the two duos. The objective of the MWDSM problem is to find a mapping so as to maximize the total weight of preserved duos. In this paper, we give a polynomial-time 6-approximation algorithm for this problem.Comment: Appeared in proceedings of the 23rd International Computing and Combinatorics Conference (COCOON 2017

    Ultra-fast current aided sintering of high coercive magnetic powders and composites

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    The paper refers to pulverization and sintering of the (Fe80Nb6B14)0.88Tb0.12 high coercive alloy. The powder was sintered using the ultra-fast current aided method. It turned out that too long discharge time leads to appearing of a soft magnetic phase and simultaneously, decrease in coercivity of the compacted powder. Nevertheless, it was possible to establish preference technology parameters, preserving magnetic hardness of the alloy. As a final test, an impact of Co-powder addition on magnetic properties was studied. The introduced soft magnetic phase (about 20 wt. %) caused about 30% increase of magnetic remanence, which is a result of direct exchange interactions between the two phases

    Online unit clustering in higher dimensions

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    We revisit the online Unit Clustering and Unit Covering problems in higher dimensions: Given a set of nn points in a metric space, that arrive one by one, Unit Clustering asks to partition the points into the minimum number of clusters (subsets) of diameter at most one; while Unit Covering asks to cover all points by the minimum number of balls of unit radius. In this paper, we work in Rd\mathbb{R}^d using the LL_\infty norm. We show that the competitive ratio of any online algorithm (deterministic or randomized) for Unit Clustering must depend on the dimension dd. We also give a randomized online algorithm with competitive ratio O(d2)O(d^2) for Unit Clustering}of integer points (i.e., points in Zd\mathbb{Z}^d, dNd\in \mathbb{N}, under LL_{\infty} norm). We show that the competitive ratio of any deterministic online algorithm for Unit Covering is at least 2d2^d. This ratio is the best possible, as it can be attained by a simple deterministic algorithm that assigns points to a predefined set of unit cubes. We complement these results with some additional lower bounds for related problems in higher dimensions.Comment: 15 pages, 4 figures. A preliminary version appeared in the Proceedings of the 15th Workshop on Approximation and Online Algorithms (WAOA 2017

    Online Multi-Coloring with Advice

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    We consider the problem of online graph multi-coloring with advice. Multi-coloring is often used to model frequency allocation in cellular networks. We give several nearly tight upper and lower bounds for the most standard topologies of cellular networks, paths and hexagonal graphs. For the path, negative results trivially carry over to bipartite graphs, and our positive results are also valid for bipartite graphs. The advice given represents information that is likely to be available, studying for instance the data from earlier similar periods of time.Comment: IMADA-preprint-c
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