OpenRaiser/Intern-Atlas huggingface dataset:
Diversity Order in ISI Channels with Single-Carrier Frequency-Domain Equalizers
Venue: arXiv cs.IT 2009
Year: 2009

This paper analyzes the diversity gain achieved by single-carrier frequency-domain equalizer (SC-FDE) in frequency selective channels, and uncovers the interplay between diversity gain $d$, channel memory length $ν$, transmission block length $L$, and the spectral efficiency $R$. We specifically show that for the class of minimum means-square error (MMSE) SC-FDE receivers, for rates $R\leq\log\frac{L}ν$ full diversity of $d=ν+1$ is achievable, while for higher rates the diversity is given by $d=\lfloor2^{-R}L\rfloor+1$. In other words, the achievable diversity gain depends not only on the channel memory length, but also on the desired spectral efficiency and the transmission block length. A similar analysis reveals that for zero forcing SC-FDE, the diversity order is always one irrespective of channel memory length and spectral efficiency. These results are supported by simulations.
Shortest Paths in Planar Graphs with Real Lengths in $O(n\log^2n/\log\log n)$ Time
Venue: arXiv cs.DM 2009
Year: 2009

Given an $n$-vertex planar directed graph with real edge lengths and with no negative cycles, we show how to compute single-source shortest path distances in the graph in $O(n\log^2n/\log\log n)$ time with O(n) space. This is an improvement of a recent time bound of $O(n\log^2n)$ by Klein et al.
Integrating the Probabilistic Models BM25/BM25F into Lucene
Venue: arXiv cs.IR 2009
Year: 2009

This document describes the BM25 and BM25F implementation using the Lucene Java Framework. Both models have stood out at TREC by their performance and are considered as state-of-the-art in the IR community. BM25 is applied to retrieval on plain text documents, that is for documents that do not contain fields, while BM25F is applied to documents with structure.
PAKE-based mutual HTTP authentication for preventing phishing attacks
Venue: arXiv cs.CR 2009
Year: 2009

This paper describes a new password-based mutual authentication protocol for Web systems which prevents various kinds of phishing attacks. This protocol provides a protection of user's passwords against any phishers even if dictionary attack is employed, and prevents phishers from imitating a false sense of successful authentication to users. The protocol is designed considering interoperability with many recent Web applications which requires many features which current HTTP authentication does not provide. The protocol is proposed as an Internet Draft submitted to IETF, and implemented in both server side (as an Apache extension) and client side (as a Mozilla-based browser and an IE-based one). The paper also proposes a new user-interface for this protocol which is always distinguishable from fake dialogs provided by phishers.
Complex Algebras of Arithmetic
Venue: arXiv cs.LO 2009
Year: 2009

An 'arithmetic circuit' is a labeled, acyclic directed graph specifying a sequence of arithmetic and logical operations to be performed on sets of natural numbers. Arithmetic circuits can also be viewed as the elements of the smallest subalgebra of the complex algebra of the semiring of natural numbers. In the present paper, we investigate the algebraic structure of complex algebras of natural numbers, and make some observations regarding the complexity of various theories of such algebras.
A note on upper bounds for the maximum span in interval edge colorings of graphs
Venue: arXiv cs.DM 2009
Year: 2009

An edge coloring of a graph $G$ with colors $1,2,..., t$ is called an interval $t$-coloring if for each $i\in \{1,2,...,t\}$ there is at least one edge of $G$ colored by $i$, the colors of edges incident to any vertex of $G$ are distinct and form an interval of integers. In 1994 Asratian and Kamalian proved that if a connected graph $G$ admits an interval $t$-coloring, then $t\leq (d+1) (Δ-1) +1$, and if $G$ is also bipartite, then this upper bound can be improved to $t\leq d(Δ-1) +1$, where $Δ$ is the maximum degree in $G$ and $d$ is the diameter of $G$. In this paper we show that these upper bounds can not be significantly improved.
Integrated Structure and Semantics for Reo Connectors and Petri Nets
Venue: arXiv cs.LO 2009
Year: 2009

In this paper, we present an integrated structural and behavioral model of Reo connectors and Petri nets, allowing a direct comparison of the two concurrency models. For this purpose, we introduce a notion of connectors which consist of a number of interconnected, user-defined primitives with fixed behavior. While the structure of connectors resembles hypergraphs, their semantics is given in terms of so-called port automata. We define both models in a categorical setting where composition operations can be elegantly defined and integrated. Specifically, we formalize structural gluings of connectors as pushouts, and joins of port automata as pullbacks. We then define a semantical functor from the connector to the port automata category which preserves this composition. We further show how to encode Reo connectors and Petri nets into this model and indicate applications to dynamic reconfigurations modeled using double pushout graph transformation.
Pigment Melanin: Pattern for Iris Recognition
Venue: arXiv cs.CV 2009
Year: 2009

Recognition of iris based on Visible Light (VL) imaging is a difficult problem because of the light reflection from the cornea. Nonetheless, pigment melanin provides a rich feature source in VL, unavailable in Near-Infrared (NIR) imaging. This is due to biological spectroscopy of eumelanin, a chemical not stimulated in NIR. In this case, a plausible solution to observe such patterns may be provided by an adaptive procedure using a variational technique on the image histogram. To describe the patterns, a shape analysis method is used to derive feature-code for each subject. An important question is how much the melanin patterns, extracted from VL, are independent of iris texture in NIR. With this question in mind, the present investigation proposes fusion of features extracted from NIR and VL to boost the recognition performance. We have collected our own database (UTIRIS) consisting of both NIR and VL images of 158 eyes of 79 individuals. This investigation demonstrates that the proposed algorithm is highly sensitive to the patterns of cromophores and improves the iris recognition rate.
A model for randomized resource allocation in decentralized wireless networks
Venue: arXiv cs.IT 2009
Year: 2009

In this paper, we consider a decentralized wireless communication network with a fixed number $u$ of frequency sub-bands to be shared among $N$ transmitter-receiver pairs. It is assumed that the number of active users is a random variable with a given probability mass function. Moreover, users are unaware of each other's codebooks and hence, no multiuser detection is possible. We propose a randomized Frequency Hopping (FH) scheme in which each transmitter randomly hops over a subset of $u$ sub-bands from transmission to transmission. We derive lower and upper bounds on the mutual information of each user and demonstrate that, for large Signal-to-Noise Ratio (SNR) values, the two bounds coincide. This observation enables us to compute the sum multiplexing gain of the system and obtain the optimum hopping strategy for maximizing this quantity. We compare the performance of the FH system with that of the Frequency Division (FD) system in terms of several performance measures and show that (depending on the probability mass function of the number of active users) the FH system can offer a significant improvement implying a more efficient usage of the spectrum.
A Decision-Optimization Approach to Quantum Mechanics and Game Theory
Venue: arXiv cs.GT 2009
Year: 2009

The fundamental laws of quantum world upsets the logical foundation of classic physics. They are completely counter-intuitive with many bizarre behaviors. However, this paper shows that they may make sense from the perspective of a general decision-optimization principle for cooperation. This principle also offers a generalization of Nash equilibrium, a key concept in game theory, for better payoffs and stability of game playing.
Randomized vs. orthogonal spectrum allocation in decentralized networks: Outage Analysis
Venue: arXiv cs.IT 2009
Year: 2009

We address a decentralized wireless communication network with a fixed number $u$ of frequency sub-bands to be shared among $N$ transmitter-receiver pairs. It is assumed that the number of users $N$ is a random variable with a given distribution and the channel gains are quasi-static Rayleigh fading. The transmitters are assumed to be unaware of the number of active users in the network as well as the channel gains and not capable of detecting the presence of other users in a given frequency sub-band. Moreover, the users are unaware of each other's codebooks and hence, no multiuser detection is possible. We consider a randomized Frequency Hopping (FH) scheme in which each transmitter randomly hops over a subset of the $u$ sub-bands from transmission to transmission. Developing a new upper bound on the differential entropy of a mixed Gaussian random vector and using entropy power inequality, we offer a series of lower bounds on the achievable rate of each user. Thereafter, we obtain lower bounds on the maximum transmission rate per user to ensure a specified outage probability at a given Signal-to-Noise Ratio (SNR) level. We demonstrate that the so-called outage capacity can be considerably higher in the FH scheme than in the Frequency Division (FD) scenario for reasonable distributions on the number of active users. This guarantees a higher spectral efficiency in FH compared to FD.
Self-Stabilizing Byzantine Asynchronous Unison
Venue: arXiv cs.DC 2009
Year: 2009

We explore asynchronous unison in the presence of systemic transient and permanent Byzantine faults in shared memory. We observe that the problem is not solvable under less than strongly fair scheduler or for system topologies with maximum node degree greater than two. We present a self-stabilizing Byzantine-tolerant solution to asynchronous unison for chain and ring topologies. Our algorithm has minimum possible containment radius and optimal stabilization time.
A Multi-stage Probabilistic Algorithm for Dynamic Path-Planning
Venue: arXiv cs.AI 2009
Year: 2009

Probabilistic sampling methods have become very popular to solve single-shot path planning problems. Rapidly-exploring Random Trees (RRTs) in particular have been shown to be efficient in solving high dimensional problems. Even though several RRT variants have been proposed for dynamic replanning, these methods only perform well in environments with infrequent changes. This paper addresses the dynamic path planning problem by combining simple techniques in a multi-stage probabilistic algorithm. This algorithm uses RRTs for initial planning and informed local search for navigation. We show that this combination of simple techniques provides better responses to highly dynamic environments than the RRT extensions.
Combining a Probabilistic Sampling Technique and Simple Heuristics to solve the Dynamic Path Planning Problem
Venue: arXiv cs.AI 2009
Year: 2009

Probabilistic sampling methods have become very popular to solve single-shot path planning problems. Rapidly-exploring Random Trees (RRTs) in particular have been shown to be very efficient in solving high dimensional problems. Even though several RRT variants have been proposed to tackle the dynamic replanning problem, these methods only perform well in environments with infrequent changes. This paper addresses the dynamic path planning problem by combining simple techniques in a multi-stage probabilistic algorithm. This algorithm uses RRTs as an initial solution, informed local search to fix unfeasible paths and a simple greedy optimizer. The algorithm is capable of recognizing when the local search is stuck, and subsequently restart the RRT. We show that this combination of simple techniques provides better responses to a highly dynamic environment than the dynamic RRT variants.
Inferring Information from Feature Diagrams to Product Line Economic Models
Venue: arXiv cs.SE 2009
Year: 2009

Existing economic models support the estimation of the costs and benefits of developing and evolving a Software Product Line (SPL) as compared to undertaking traditional software development approaches. In addition, Feature Diagrams (FDs) are a valuable tool to scope the domain of a SPL. This paper proposes an algorithm to calculate, from a FD, the following information for economic models: the total number of products of a SPL, the SPL homogeneity and the commonality of the SPL requirements. The algorithm running time belongs to the complexity class $O(f^42^c)$. In contrast to related work, the algorithm is free of dependencies on off-the-self tools and is generally specified for an abstract FD notation, that works as a pivot language for most of the available notations for feature modeling.
New Algorithmic Approaches for Computing Optimal Network Paths with Several Types of QoS Constraints
Venue: arXiv cs.DS 2009
Year: 2009

The problem of efficiently delivering data within networks is very important nowadays, especially in the context of the large volumes of data which are being produced each year and of the increased data access needs of the users. Efficient data delivery strategies must satisfy several types of Quality of Service (QoS) constraints which are imposed by the data consumers. One possibility of achieving this goal (particularly in the case of in-order data transfers) is to choose a satisfactory network delivery path. In this paper we present novel algorithmic approaches for computing optimal network paths which satisfy several types of (QoS) constraints.
Neural-estimator for the surface emission rate of atmospheric gases
Venue: arXiv cs.NE 2009
Year: 2009

The emission rate of minority atmospheric gases is inferred by a new approach based on neural networks. The neural network applied is the multi-layer perceptron with backpropagation algorithm for learning. The identification of these surface fluxes is an inverse problem. A comparison between the new neural-inversion and regularized inverse solution id performed. The results obtained from the neural networks are significantly better. In addition, the inversion with the neural netwroks is fster than regularized approaches, after training.
An expected-case sub-cubic solution to the all-pairs shortest path problem in R
Venue: arXiv cs.DS 2009
Year: 2009

It has been shown by Alon et al. that the so-called 'all-pairs shortest-path' problem can be solved in O((MV)^2.688 * log^3(V)) for graphs with V vertices, with integer distances bounded by M. We solve the more general problem for graphs in R (assuming no negative cycles), with expected-case running time O(V^2.5 * log(V)). While our result appears to violate the Omega(V^3) requirement of "Funny Matrix Multiplication" (due to Kerr), we find that it has a sub-cubic expected time solution subject to reasonable conditions on the data distribution. The expected time solution arises when certain sub-problems are uncorrelated, though we can do better/worse than the expected-case under positive/negative correlation (respectively). Whether we observe positive/negative correlation depends on the statistics of the graph in question. In practice, our algorithm is significantly faster than Floyd-Warshall, even for dense graphs.
Comparative Study Of Congestion Control Techniques In High Speed Networks
Venue: arXiv cs.NI 2009
Year: 2009

Congestion in network occurs due to exceed in aggregate demand as compared to the accessible capacity of the resources. Network congestion will increase as network speed increases and new effective congestion control methods are needed, especially to handle bursty traffic of todays very high speed networks. Since late 90s numerous schemes i.e. [1]...[10] etc. have been proposed. This paper concentrates on comparative study of the different congestion control schemes based on some key performance metrics. An effort has been made to judge the performance of Maximum Entropy (ME) based solution for a steady state GE/GE/1/N censored queues with partial buffer sharing scheme against these key performance metrics.
Performance analysis of Non Linear Filtering Algorithms for underwater images
Venue: arXiv cs.MM 2009
Year: 2009

Image filtering algorithms are applied on images to remove the different types of noise that are either present in the image during capturing or injected in to the image during transmission. Underwater images when captured usually have Gaussian noise, speckle noise and salt and pepper noise. In this work, five different image filtering algorithms are compared for the three different noise types. The performances of the filters are compared using the Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE). The modified spatial median filter gives desirable results in terms of the above two parameters for the three different noise. Forty underwater images are taken for study.
Designing Kernel Scheme for Classifiers Fusion
Venue: arXiv cs.LG 2009
Year: 2009

In this paper, we propose a special fusion method for combining ensembles of base classifiers utilizing new neural networks in order to improve overall efficiency of classification. While ensembles are designed such that each classifier is trained independently while the decision fusion is performed as a final procedure, in this method, we would be interested in making the fusion process more adaptive and efficient. This new combiner, called Neural Network Kernel Least Mean Square1, attempts to fuse outputs of the ensembles of classifiers. The proposed Neural Network has some special properties such as Kernel abilities,Least Mean Square features, easy learning over variants of patterns and traditional neuron capabilities. Neural Network Kernel Least Mean Square is a special neuron which is trained with Kernel Least Mean Square properties. This new neuron is used as a classifiers combiner to fuse outputs of base neural network classifiers. Performance of this method is analyzed and compared with other fusion methods. The analysis represents higher performance of our new method as opposed to others.
Web Document Analysis for Companies Listed in Bursa Malaysia
Venue: arXiv cs.IR 2009
Year: 2009

This paper discusses a research on web document analysis for companies listed on Bursa Malaysia which is the forerunner of financial and investment center in Malaysia. Data set used in this research are from the company web documents listed in the Main Board and Second Board on Bursa Malaysia. This research has used the Web Resources Extraction System which was developed by the research group mainly to extract information for the web documents involved. Our research findings have shown that the level of website usage among the companies on Bursa Malaysia is still minimal. Furthermore, research has also found that 60.02 percent of the image files are utilized making it the most used type of file in creating websites.
XML Multidimensional Modelling and Querying
Venue: arXiv cs.DB 2009
Year: 2009

As XML becomes ubiquitous and XML storage and processing becomes more efficient, the range of use cases for these technologies widens daily. One promising area is the integration of XML and data warehouses, where an XML-native database stores multidimensional data and processes OLAP queries written in the XQuery interrogation language. This paper explores issues arising in the implementation of such a data warehouse. We first compare approaches for multidimensional data modelling in XML, then describe how typical OLAP queries on these models can be expressed in XQuery. We then show how, regardless of the model, the grouping features of XQuery 1.1 improve performance and readability of these queries. Finally, we evaluate the performance of query evaluation in each modelling choice using the eXist database, which we extended with a grouping clause implementation.
A fast randomized algorithm for orthogonal projection
Venue: arXiv cs.NA 2009
Year: 2009

We describe an algorithm that, given any full-rank matrix A having fewer rows than columns, can rapidly compute the orthogonal projection of any vector onto the null space of A, as well as the orthogonal projection onto the row space of A, provided that both A and its adjoint can be applied rapidly to arbitrary vectors. As an intermediate step, the algorithm solves the overdetermined linear least-squares regression involving the adjoint of A (and so can be used for this, too). The basis of the algorithm is an obvious but numerically unstable scheme; suitable use of a preconditioner yields numerical stability. We generate the preconditioner rapidly via a randomized procedure that succeeds with extremely high probability. In many circumstances, the method can accelerate interior-point methods for convex optimization, such as linear programming (Ming Gu, personal communication).
Algebraic Change-Point Detection
Venue: arXiv cs.NA 2009
Year: 2009

Elementary techniques from operational calculus, differential algebra, and noncommutative algebra lead to a new approach for change-point detection, which is an important field of investigation in various areas of applied sciences and engineering. Several successful numerical experiments are presented.
The university-industry knowledge relationship: Analyzing patents and the science base of technologies
Venue: arXiv cs.DL 2009
Year: 2009

Via the Internet, information scientists can obtain cost-free access to large databases in the hidden or deep web. These databases are often structured far more than the Internet domains themselves. The patent database of the U.S. Patent and Trade Office is used in this study to examine the science base of patents in terms of the literature references in these patents. University-based patents at the global level are compared with results when using the national economy of the Netherlands as a system of reference. Methods for accessing the on-line databases and for the visualization of the results are specified. The conclusion is that 'biotechnology' has historically generated a model for theorizing about university-industry relations that cannot easily be generalized to other sectors and disciplines.
Conception d'un outil d'aide à l'indexation de ressources pédagogiques - Extraction automatique des thématiques et des mots-clefs de documents UNIT
Venue: arXiv cs.IR 2009
Year: 2009

Indexing learning documents using the Learning Object Metadata (LOM) is often carried out manually by archivists. Filling out the LOM fields is a long and difficult task, requiring a complete reading and a full knowledge on the topic dealt within the document. In this paper, we present an innovative model and method to assist the archivists in finding the important concepts and keywords of a learning document. The application is performed using wikipedia's category links.
The Mutual Information of University-Industry-Government Relations: An Indicator of the Triple Helix Dynamics
Venue: arXiv cs.CY 2009
Year: 2009

University-industry-government relations provide a networked infrastructure for knowledge-based innovation systems. This infrastructure organizes the dynamic fluxes locally and the knowledge base remains emergent given these conditions. Whereas the relations between the institutions can be measured as variables, the interacting fluxes generate a probabilistic entropy. The mutual information among the three institutional dimensions provides us with an indicator of this entropy. When this indicator is negative, self-organization can be expected. The self-organizing dynamic may temporarily be stabilized in the overlay of communications among the carrying agencies. The various dynamics of Triple Helix relations at the global and national levels, in different databases, and in different regions of the world, are distinguished by applying this indicator to scientometric and webometric data.