5,366 research outputs found
Orchestrating Forest Policy in Italy: Mission Impossible?
In the Italian political and economic agenda the forest sector occupies a marginal role. The forest sector in Italy is characterized by a high institutional fragmentation and centralized decision-making processes dominated by Public Forest Administrations. Public participation in forest policy processes has been implemented since the 1990s at national, regional and local levels in several cases. However, today no significant changes have been observed in the overall governance of the forest sector and stakeholders' involvement in Italian forest policy decision-making is still rather limited. The aims of this paper are to describe the state of forest-related participatory processes in Italy at various levels (national, regional and local) and identify which factors and actors hinder or support the establishment and implementation of participatory forest-related processes in the country. The forest-related participatory processes are analyzed adopting a qualitative-based approach and interpreting interactive, complex and non-linear participatory processes through the lens of panarchy theory
A Formal Approach to Exploiting Multi-Stage Attacks based on File-System Vulnerabilities of Web Applications (Extended Version)
Web applications require access to the file-system for many different tasks.
When analyzing the security of a web application, secu- rity analysts should
thus consider the impact that file-system operations have on the security of
the whole application. Moreover, the analysis should take into consideration
how file-system vulnerabilities might in- teract with other vulnerabilities
leading an attacker to breach into the web application. In this paper, we first
propose a classification of file- system vulnerabilities, and then, based on
this classification, we present a formal approach that allows one to exploit
file-system vulnerabilities. We give a formal representation of web
applications, databases and file- systems, and show how to reason about
file-system vulnerabilities. We also show how to combine file-system
vulnerabilities and SQL-Injection vulnerabilities for the identification of
complex, multi-stage attacks. We have developed an automatic tool that
implements our approach and we show its efficiency by discussing several
real-world case studies, which are witness to the fact that our tool can
generate, and exploit, complex attacks that, to the best of our knowledge, no
other state-of-the-art-tool for the security of web applications can find
A Fast and Efficient Incremental Approach toward Dynamic Community Detection
Community detection is a discovery tool used by network scientists to analyze
the structure of real-world networks. It seeks to identify natural divisions
that may exist in the input networks that partition the vertices into coherent
modules (or communities). While this problem space is rich with efficient
algorithms and software, most of this literature caters to the static use-case
where the underlying network does not change. However, many emerging real-world
use-cases give rise to a need to incorporate dynamic graphs as inputs.
In this paper, we present a fast and efficient incremental approach toward
dynamic community detection. The key contribution is a generic technique called
, which examines the most recent batch of changes made to an
input graph and selects a subset of vertices to reevaluate for potential
community (re)assignment. This technique can be incorporated into any of the
community detection methods that use modularity as its objective function for
clustering. For demonstration purposes, we incorporated the technique into two
well-known community detection tools. Our experiments demonstrate that our new
incremental approach is able to generate performance speedups without
compromising on the output quality (despite its heuristic nature). For
instance, on a real-world network with 63M temporal edges (over 12 time steps),
our approach was able to complete in 1056 seconds, yielding a 3x speedup over a
baseline implementation. In addition to demonstrating the performance benefits,
we also show how to use our approach to delineate appropriate intervals of
temporal resolutions at which to analyze an input network
The three-dimensional Ising model: A paradigm of liquid-vapor coexistence in nuclear multifragmentation
Clusters in the three-dimensional Ising model rigorously obey reducibility
and thermal scaling up to the critical temperature. The barriers extracted from
Arrhenius plots depend on the cluster size as where
is a critical exponent relating the cluster size to the cluster
surface. All the Arrhenius plots collapse into a single Fisher-like scaling
function indicating liquid-vapor-like phase coexistence and the univariant
equilibrium between percolating clusters and finite clusters. The compelling
similarity with nuclear multifragmentation is discussed.Comment: (4 pages, 4 figures
Transformação dos principais usos da floresta no município de Moju, nordeste paraense.
As reflexões aqui apresentadas foram resultantes de uma pesquisa realizada na comunidade Santa Maria, uma das comunidades componentes do Assentamento Olho D?Água II, município de Moju, estado do Pará. O objetivo do artigo é analisar as transformações vivenciadas por um grupo de agricultores quanto ao uso da floresta, mais especificamente as associadas à obtenção de caças e à realização das roças, após a mudança da condição de uso comum (posseiros) para o uso privado (assentados) a partir da implantação do assentamento em 2002. Os resultados apontam que ocorreram transformações nas dinâmicas de uso dos recursos com a intensificação do cultivo de roças e a diminuição da obtenção de caças devido à grande dificuldade em obtê-las, em decorrência das novas condições de acesso privado à terra e ao aumento demográfico cuja demanda por caça supera em muito a oferta dos animais
On generalized cluster algorithms for frustrated spin models
Standard Monte Carlo cluster algorithms have proven to be very effective for
many different spin models, however they fail for frustrated spin systems.
Recently a generalized cluster algorithm was introduced that works extremely
well for the fully frustrated Ising model on a square lattice, by placing bonds
between sites based on information from plaquettes rather than links of the
lattice. Here we study some properties of this algorithm and some variants of
it. We introduce a practical methodology for constructing a generalized cluster
algorithm for a given spin model, and investigate apply this method to some
other frustrated Ising models. We find that such algorithms work well for
simple fully frustrated Ising models in two dimensions, but appear to work
poorly or not at all for more complex models such as spin glasses.Comment: 34 pages in RevTeX. No figures included. A compressed postscript file
for the paper with figures can be obtained via anonymous ftp to
minerva.npac.syr.edu in users/paulc/papers/SCCS-527.ps.Z. Syracuse University
NPAC technical report SCCS-52
Semantic disambiguation and contextualisation of social tags
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-28509-7_18This manuscript is an extended version of the paper ‘cTag: Semantic Contextualisation of Social Tags’, presented at the 6th International Workshop on Semantic Adaptive Social Web (SASWeb 2011).We present an algorithmic framework to accurately and efficiently identify the semantic meanings and contexts of social tags within a particular folksonomy. The framework is used for building contextualised tag-based user and item profiles. We also present its implementation in a system called cTag, with which we preliminary analyse semantic meanings and contexts of tags belonging to Delicious and MovieLens folksonomies. The analysis includes a comparison between semantic similarities obtained for pairs of tags in Delicious folksonomy, and their semantic distances in the whole Web, according to co-occurrence based metrics computed with results of a Web search engine.This work was supported by the Spanish Ministry of Science
and Innovation (TIN2008-06566-C04-02), and Universidad Autónoma de Madrid
(CCG10-UAM/TIC-5877
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