pinecone/core-2020-05-10-deduplication huggingface dataset:
Strict Forest Reserve Research in the Margin of the Carpathians, the Vár-hegy Case-Study

Sixteen forest reserves are situated in the northern part of Hungary which belongs to the Carpathian region according to EURAC delimitation (Ruffini et al. 2006). These Hungarian forest reserves expand the natural forest remnant/forest reserve net of the Carpathians towards the lower hilly region, representing the deciduous beech and oak forest belts near their lower (xeric) distribution limits. This paper outlines the Hungarian forest reserves belonging to the Carpathian region and the preliminary results of current projects in the Vár-hegy Forest Reserve (Bükk Mts., Hungary) as a case study. The alteration of tree species composition was investigated here based on the reconstruction of forest history in the previous 130 years (management period) and analyses of forest stand inventory. In another project CO2 sequestration changes of these forest stands were modeled since the clear-cutting in the 1880th and carbon stored in the forest ecosystem compartments was estimated. Our results show that the forest reserve stands are presently in a transition state from the managed forest towards a more natural mixed forest with several age-classes
Characteristics of the Dynamic of Mobile Networks

International audienceWe propose in this paper a novel framework for the study of dynamic mobility networks. We address the characterization of dynamics by proposing an in-depth description and analysis of two real-world data sets. We show in particular that edges creation and deletion processes are independent of other graph properties and that such networks exhibit a large number of possible configurations, from sparse to dense. From those observations, we propose simple yet very accurate models that allow to generate random mobility graphs with similar temporal behavior as the one observed in experimental data
Introduction to Categories and Categorical Logic

Working paper, submitted at Cornell University Library Archive on the 7th of February 2011. Available via http://arxiv.org/abs/1102.1313v196 pages96 pagesThe aim of these notes is to provide a succinct, accessible introduction to some of the basic ideas of category theory and categorical logic. The notes are based on a lecture course given at Oxford over the past few years. They contain numerous exercises, and hopefully will prove useful for self-study by those seeking a first introduction to the subject, with fairly minimal prerequisites. The coverage is by no means comprehensive, but should provide a good basis for further study; a guide to further reading is included. The main prerequisite is a basic familiarity with the elements of discrete mathematics: sets, relations and functions. An Appendix contains a summary of what we will need, and it may be useful to review this first. In addition, some prior exposure to abstract algebra - vector spaces and linear maps, or groups and group homomorphisms - would be helpful
A survey of graphical languages for monoidal categories

This article is intended as a reference guide to various notions of monoidal
categories and their associated string diagrams. It is hoped that this will be
useful not just to mathematicians, but also to physicists, computer scientists,
and others who use diagrammatic reasoning. We have opted for a somewhat
informal treatment of topological notions, and have omitted most proofs.
Nevertheless, the exposition is sufficiently detailed to make it clear what is
presently known, and to serve as a starting place for more in-depth study.
Where possible, we provide pointers to more rigorous treatments in the
literature. Where we include results that have only been proved in special
cases, we indicate this in the form of caveats
Dense matter in compact stars - A pedagogical introduction

Cold and dense nuclear and/or quark matter can be found in the interior of
compact stars. It is very challenging to determine the ground state and
properties of this matter because of the strong-coupling nature of QCD. I give
a pedagogical introduction to microscopic calculations based on
phenomenological models, effective theories, and perturbative QCD. I discuss
how the results of these calculations can be related to astrophysical
observations to potentially rule out or confirm candidate phases of dense
matter.Comment: 138+10 pages, v2: small modifications, typos fixed, Figs. 2.1 and 3.7
  slightly changed; to appear in Lect. Notes Phys. (Springer), ISBN
  978-3-642-12865-
A Flow Scheduler Architecture

International audienceScheduling flows in the Internet has sprouted much interest in the research community leading to the development of many queueing models, capitalizing on the heavy-tail property of flow size distribution. Theoretical studies have shown that 'size-based' schedulers improve the delay of small flows without almost no performance degradation to large flows. On the practical side, the issues in taking such schedulers to implementation have hardly been studied. This work looks into practical aspects of making size-based scheduling feasible in future Internet. In this context, we propose a flow scheduler architecture comprising three modules -- Size-based scheduling, Threshold-based sampling and Knockout buffer policy -- for improving the performance of flows in the Internet. Unlike earlier works, we analyze the performance using five different performance metrics, and through extensive simulations show the goodness of this architecture
Routing Protocol for Anycast Communications in a Wireless Sensor Network

International audienceIn wireless sensor networks, there is usually a sink which gathers data from the battery-powered sensor nodes. As sensor nodes around the sink consume their energy faster than the other nodes, several sinks have to be deployed to increase the network lifetime. In this paper, we motivate the need of anycast communications in wireless networks, where all the sinks are identical and can gather data from any source. To reduce interference and congestion areas on the wireless medium, the path from a source to a sink has to be distant from the path connecting another source to another sink. We show that determining distant paths from sources to sinks is an NP-hard problem, and we propose a linear formulation in order to obtain optimal solutions. Then, we propose a sink selection and routing protocol called S4 and based on realistic assumptions and we evaluate it through simulations. Finally, we conclude that anycast routing protocols in wireless sensor networks should not compute paths independently for each source, but rather consider all the sources simultaneously
Preventing pollution attacks in multi-source network coding

Network coding is a method for achieving channel capacity in networks. The key idea is to allow network routers to linearly mix packets as they traverse the network so that recipients receive linear combinations of packets. Network coded systems are vulnerable to pollution attacks where a single malicious node floods the network with bad packets and prevents the receiver from decoding correctly. Cryptographic defenses to these problems are based on homomorphic signatures and MACs. These proposals, however, cannot handle mixing of packets from multiple sources, which is needed to achieve the full benefits of network coding. In this paper we address integrity of multi-source mixing. We propose a security model for this setting and provide a generic construction
Faster pairing computations on curves with high-degree twists

Research on eﬃcient pairing implementation has focussed on \ud
reducing the loop length and on using high-degree twists. Existence of \ud
twists of degree larger than 2 is a very restrictive criterion but luckily \ud
constructions for pairing-friendly elliptic curves with such twists exist. \ud
In fact, Freeman, Scott and Teske showed in their overview paper that \ud
often the best known methods of constructing pairing-friendly elliptic \ud
curves over ﬁelds of large prime characteristic produce curves that admit \ud
twists of degree 3, 4 or 6. \ud
A few papers have presented explicit formulas for the doubling and the \ud
addition step in Miller’s algorithm, but the optimizations were all done \ud
for the Tate pairing with degree-2 twists, so the main usage of the high- \ud
degree twists remained incompatible with more eﬃcient formulas. \ud
In this paper we present eﬃcient formulas for curves with twists of degree \ud
2, 3, 4 or 6. These formulas are signiﬁcantly faster than their predecessors. \ud
We show how these faster formulas can be applied to Tate and ate pairing \ud
variants, thereby speeding up all practical suggestions for eﬃcient pairing \ud
implementations over ﬁelds of large characteristic
Constant size ciphertexts in threshold attribute-based encryption

Attribute-based cryptography has emerged in the last years as a promising primitive for digital security. For instance, it provides good solutions to the problem of anonymous access control. In a ciphertextpolicy attribute-based encryption scheme, the secret keys of the users depend on their attributes. When encrypting a message, the sender chooses which subset of attributes must be held by a receiver in order to be able to decrypt.\ud
All current attribute-based encryption schemes that admit reasonably expressive decryption policies produce ciphertexts whose size depends at least linearly on the number of attributes involved in the policy. In this paper we propose the first scheme whose ciphertexts have constant size.\ud
Our scheme works for the threshold case: users authorized to decrypt are those who hold at least t attributes among a certain universe of attributes, for some threshold t chosen by the sender. An extension to the\ud
case of weighted threshold decryption policies is possible. The security of the scheme against selective chosen plaintext attacks can be proven in the standard model by reduction to the augmented multi-sequence of exponents decisional Diffie-Hellman (aMSE-DDH) problem.Postprint (published version
Lattice mixing and vanishing trapdoors : a framework for fully secure short signatures and more

We propose a framework for adaptive security from hard random lattices in the standard model. Our approach borrows from the recent Agrawal-Boneh-Boyen families of lattices, which can admit reliable and punctured trapdoors, respectively used in reality and in simulation. We extend this idea to make the simulation trapdoors cancel not for a specific forgery but on a non-negligible subset of the possible challenges. Conceptually, we build a compactly representable, large family of input-dependent “mixture” lattices, set up with trapdoors that “vanish” for a secret subset which we hope the forger will target. Technically, we tweak the lattice structure to achieve “naturally nice” distributions for arbitrary choices of subset size. The framework is very general. Here we obtain fully secure signatures, and also IBE, that are compact, simple, and elegant.\u
A Regulatory Model for Context-Aware Abstract Framework

Proceedings of: 23rd International Conference on Industrial Engineering and
Other Applications of Applied Intelligent Systems, IEA/AIE 2010, Cordoba,
Spain, June 1-4, 2010.This paper presents a general framework to define a context aware application and analyzes social guarantees to be considered to develop this kind of applications following legal assumptions as privacy, human rights, etc. We
present a review of legal issues in biometric user identification where several
legal aspects have been developed in European Union regulation and a general
framework to define context aware applications. As main result, paper presents
a legal framework to be taken into account in any context-based application to
ensure a harmonious and coherent system for the protection of fundamental
rights.This work was supported in part by Projects CICYT TIN2008-06742-C02-02/TSI, CICYT
TEC2008-06732-C02-02/TEC, CAM CONTEXTS (S2009/TIC-1485) and DPS2008-07029-
C02-02.Publicad
Exploring the performance of resampling strategies for the class imbalance problem

The present paper studies the influence of two distinct factors on the performance of some resampling strategies for handling imbalanced data sets. In particular, we focus on the nature of the classifier used, along with the ratio between minority and majority classes. Experiments using eight different classifiers show that the most significant differences are for data sets with low or moderate imbalance: over-sampling clearly appears as better than under-sampling for local classifiers, whereas some under-sampling strategies outperform over-sampling when employing classifiers with global learning
Algorithmic decision of syllogisms

23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligence Systems, IEA/AIE 2010; Cordoba; Spain; 1 June 2010 through 4 June 2010A syllogism, also known as a rule of inference, is a formal logical scheme used to draw a conclusion from a set of premises. In a categorical syllogisms, every premise and conclusion is given in form a of quantified relationship between two objects. The syllogistic system consists of systematically combined premises and conclusions to so called figures and moods. The syllogistic system is a theory for reasoning, developed by Aristotle, who is known as one of the most important contributors of the western thought and logic. Since Aristotle, philosophers and sociologists have successfully modelled human thought and reasoning with syllogistic structures. However, a major lack was that the mathematical properties of the whole syllogistic system could not be fully revealed by now. To be able to calculate any syllogistic property exactly, by using a single algorithm, could indeed facilitate modelling possibly any sort of consistent, inconsistent or approximate human reasoning. In this paper we present such an algorithm
Ensembles of probability estimation trees for customer churn prediction

Customer churn prediction is one of the most, important elements tents of a company's Customer Relationship Management, (CRM) strategy In tins study, two strategies are investigated to increase the lift. performance of ensemble classification models, i.e (1) using probability estimation trees (PETs) instead of standard decision trees as base classifiers; and (n) implementing alternative fusion rules based on lift weights lot the combination of ensemble member's outputs Experiments ale conducted lot font popular ensemble strategics on five real-life chin n data sets In general, the results demonstrate how lift performance can be substantially improved by using alternative base classifiers and fusion tides However: the effect vanes lot the (Idol cut ensemble strategies lit particular, the results indicate an increase of lift performance of (1) Bagging by implementing C4 4 base classifiets. (n) the Random Subspace Method (RSM) by using lift-weighted fusion rules, and (in) AdaBoost, by implementing both
Solving Non-Stationary Bandit Problems by Random Sampling from Sibling Kalman Filters

Published version of an article from Lecture Notes in Computer Science. Also available at SpringerLink: http://dx.doi.org/10.1007/978-3-642-13033-5_21The multi-armed bandit problem is a classical optimization problem where an agent sequentially pulls one of multiple arms attached to a gambling machine, with each pull resulting in a random reward. The reward distributions are unknown, and thus, one must balance between exploiting existing knowledge about the arms, and obtaining new information. Dynamically changing (non-stationary) bandit problems are particularly challenging because each change of the reward distributions may progressively degrade the performance of any fixed strategy. Although computationally intractable in many cases, Bayesian methods provide a standard for optimal decision making. This paper proposes a novel solution scheme for bandit problems with non-stationary normally distributed rewards. The scheme is inherently Bayesian in nature, yet avoids computational intractability by relying simply on updating the hyper parameters of sibling Kalman Filters, and on random sampling from these posteriors. Furthermore, it is able to track the better actions, thus supporting non-stationary bandit problems. Extensive experiments demonstrate that our scheme outperforms recently proposed bandit playing algorithms, not only in non-stationary environments, but in stationary environments also. Furthermore, our scheme is robust to inexact parameter settings. We thus believe that our methodology opens avenues for obtaining improved novel solutions
A Learning Automata Based Solution to Service Selection in Stochastic Environments

Published version of a paper published in the book: Trends in Applied Intelligent Systems. Also available on SpringerLink: http://dx.doi.org/10.1007/978-3-642-13033-5_22With the abundance of services available in today’s world, identifying those of high quality is becoming increasingly difficult. Reputation systems can offer generic recommendations by aggregating user provided opinions about service quality, however, are prone to ballot stuffing and badmouthing . In general, unfair ratings may degrade the trustworthiness of reputation systems, and changes in service quality over time render previous ratings unreliable. In this paper, we provide a novel solution to the above problems based on Learning Automata (LA), which can learn the optimal action when operating in unknown stochastic environments. Furthermore, they combine rapid and accurate convergence with low computational complexity. In additional to its computational simplicity, unlike most reported approaches, our scheme does not require prior knowledge of the degree of any of the above mentioned problems with reputation systems. Instead, it gradually learns which users provide fair ratings, and which users provide unfair ratings, even when users unintentionally make mistakes. Comprehensive empirical results show that our LA based scheme efficiently handles any degree of unfair ratings (as long as ratings are binary). Furthermore, if the quality of services and/or the trustworthiness of users change, our scheme is able to robustly track such changes over time. Finally, the scheme is ideal for decentralized processing. Accordingly, we believe that our LA based scheme forms a promising basis for improving the performance of reputation systems in general
License Plate Detection based on Genetic Neural Networks, Morphology, and Active Contours

This paper describes a new method for License Plate Detection based on Genetic Neural Networks, Morphology, and Active Contours. Given an image is divided into several virtual regions sized 10×10 pixels, applying several performance algorithms within each virtual region, algorithms such as edge detection, histograms, and binary thresholding, etc. These results are used as inputs for a Genetic Neural Network, which provides the initial selection for the probable situation of the license plate. Further reﬁnement is applied using active contours to ﬁt the output tightly to the license plate. With a small and well–chosen subset of images, the system is able to deal with a large variety of images with real–world characteristics obtaining great precision in the detection. The eﬀectiveness for the proposed method is very high (97%). This method will be the ﬁrst stage of a surveillance system which takes into account not only the actual license plate but also the model of the car to determine if a car should be taken as a threat
Strategies for incorporating knowledge defects and path length in trust aggregation

The ability for a user to accurately estimate the amount of trust to be placed in a peer user is gaining more and more attention in social network applications. Trust aggregation provides this ability by identifying paths that connect users in the network, and by merging trust opinions expressed by users along these paths. However, as individual trust opinions are not always based on perfect knowledge, and since the quality of a trust estimation propagated along a given path may diminish as its length increases, mechanisms are needed to handle these imperfections. In this paper, we propose a set of trust aggregation operators that take into account; knowledge defects and path length. We investigate their properties, and discuss how they may be implemented in practice, taking into account; characteristics of the network such as the availability of a central authority, or the need to preserve users' privacy by not publically disclosing their trust information
Finding an Evolutionarily Stable Strategy in Agent Reputation and Trust (ART) 2007 Competition

Proceedings of: 23rd International Conference on Industrial Engineering and Other Applications of Applied intelligent Systems, IEA/AIE 2010, Cordoba, Spain, June 1-4, 2010Our proposal is to apply a Game Theoretic approach to the games played in Agent Reputation and Trust Final Competitions. Using such testbed, three international competitions were successfully carried out jointly with the last AAMAS international Conferences. The corresponding way to define the winner of such competitions was to run a game with all the participants (16). Our point is that such game does not represent a complete way to determine the best trust/reputation strategy, since it is not proved that such strategy is evolutionarily stable. Specifically we prove that when the strategy of the winner of the two first international competitions (2006 and 2007) becomes dominant, it is defeated by other participant trust strategies. Then we found out (through a repeated game definition) the right equilibrium of trust strategies that is evolutionarily stable. This kind of repeated game has to be taken into account in the evaluation of trust strategies, and this conclusion would improve the way trust strategies have to be compared.This work was supported in part by Projects CICYT TIN2008-06742-C02-02/
TSI, CICYT TEC2008-06732-C02-02/TEC, SINPROB, CAM MADRINET
S-0505/TIC/0255 and DPS2008-07029-C02-02.Publicad
Air Traffic Control: A Local Approach to the Trajectory Segmentation Issue

Proceedings of: 23rd International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA-AIE 2010) Córdoba-Spain, June 04-06, 2010This paper presents a new approach for trajectory segmentation in the area of Air Traffic Control, as a basic tool for offline validation with recorded opportunity traffic data. Our approach uses local information to classify each measurement individually, constructing the final segments over these classified samples as the final solution of the process. This local classification is based on a domain transformation using motion models to identify the deviations at a local scale, as an alternative to other global approaches based on combinatorial analysis over the trajectory segmentation domain.This work was supported in part by Projects CICYT TIN2008-06742-C02-02/TSI,
CICYT TEC2008-06732-C02-02/TEC, CAM CONTEXTS (S2009/TIC-1485) and
DPS2008-07029-C02-02.Publicad