OpenRaiser/Intern-Atlas huggingface dataset:
A unified characterization of generalized information and certainty measures
Venue: arXiv cs.IT 2013
Year: 2013

In this paper we consider the axiomatic characterization of information and certainty measures in a unified way. We present the general axiomatic system which captures the common properties of a large number of the measures previously considered by numerous authors. We provide the corresponding characterization theorems and define a new generalized measure called the Inforcer, which is the quasi-linear mean of the function associated to the event probability following the general composition law. In particular, we pay attention to the polynomial composition and the corresponding polynomially composable Inforcer measure. The most common measures appearing in literature can be obtained by specific choice of parameters appearing in our generic measures and they are listed in tables.
Laplacian Spectral Properties of Graphs from Random Local Samples
Venue: arXiv cs.SI 2013
Year: 2013

The Laplacian eigenvalues of a network play an important role in the analysis of many structural and dynamical network problems. In this paper, we study the relationship between the eigenvalue spectrum of the normalized Laplacian matrix and the structure of `local' subgraphs of the network. We call a subgraph \emph{local} when it is induced by the set of nodes obtained from a breath-first search (BFS) of radius $r$ around a node. In this paper, we propose techniques to estimate spectral properties of the normalized Laplacian matrix from a random collection of induced local subgraphs. In particular, we provide an algorithm to estimate the spectral moments of the normalized Laplacian matrix (the power-sums of its eigenvalues). Moreover, we propose a technique, based on convex optimization, to compute upper and lower bounds on the spectral radius of the normalized Laplacian matrix from local subgraphs. We illustrate our results studying the normalized Laplacian spectrum of a large-scale online social network.
Message and time efficient multi-broadcast schemes
Venue: arXiv cs.DC 2013
Year: 2013

We consider message and time efficient broadcasting and multi-broadcasting in wireless ad-hoc networks, where a subset of nodes, each with a unique rumor, wish to broadcast their rumors to all destinations while minimizing the total number of transmissions and total time until all rumors arrive to their destination. Under centralized settings, we introduce a novel approximation algorithm that provides almost optimal results with respect to the number of transmissions and total time, separately. Later on, we show how to efficiently implement this algorithm under distributed settings, where the nodes have only local information about their surroundings. In addition, we show multiple approximation techniques based on the network collision detection capabilities and explain how to calibrate the algorithms' parameters to produce optimal results for time and messages.
Text Classification For Authorship Attribution Analysis
Venue: arXiv cs.DL 2013
Year: 2013

Authorship attribution mainly deals with undecided authorship of literary texts. Authorship attribution is useful in resolving issues like uncertain authorship, recognize authorship of unknown texts, spot plagiarism so on. Statistical methods can be used to set apart the approach of an author numerically. The basic methodologies that are made use in computational stylometry are word length, sentence length, vocabulary affluence, frequencies etc. Each author has an inborn style of writing, which is particular to himself. Statistical quantitative techniques can be used to differentiate the approach of an author in a numerical way. The problem can be broken down into three sub problems as author identification, author characterization and similarity detection. The steps involved are pre-processing, extracting features, classification and author identification. For this different classifiers can be used. Here fuzzy learning classifier and SVM are used. After author identification the SVM was found to have more accuracy than Fuzzy classifier. Later combined the classifiers to obtain a better accuracy when compared to individual SVM and fuzzy classifier.
Global mibility and handover management for heterogeneous network in VANET
Venue: arXiv cs.NI 2013
Year: 2013

Now a days Vehicular Ad hoc Network is an emerging technology. Mobility management is one of the most challenging research issues for Vehicular Ad hoc Network to support variety of intelligent transportation system applications. Vehicular Ad hoc Networks are getting importance for inter-vehicle communication, because they allow the communication among vehicles without any infrastructure, configuration effort, and without the high costs of cellular networks. Besides local data exchange, vehicular applications may be used to accessing Internet services. The access is provided by Internet gateways located on the site of roadside. However, the Internet integration requires a respective mobility support of the vehicular ad hoc network. In this paper we will study about the network mobility approach in vehicular ad hoc network; the model will describe the movement of vehicles from one network to other network. The proposed handover scheme reduces the handover latency, packet loss signaling overhead.
Learning Tensors in Reproducing Kernel Hilbert Spaces with Multilinear Spectral Penalties
Venue: arXiv cs.LG 2013
Year: 2013

We present a general framework to learn functions in tensor product reproducing kernel Hilbert spaces (TP-RKHSs). The methodology is based on a novel representer theorem suitable for existing as well as new spectral penalties for tensors. When the functions in the TP-RKHS are defined on the Cartesian product of finite discrete sets, in particular, our main problem formulation admits as a special case existing tensor completion problems. Other special cases include transfer learning with multimodal side information and multilinear multitask learning. For the latter case, our kernel-based view is instrumental to derive nonlinear extensions of existing model classes. We give a novel algorithm and show in experiments the usefulness of the proposed extensions.
Do System Test Cases Grow Old?
Venue: arXiv cs.SE 2013
Year: 2013

Companies increasingly use either manual or automated system testing to ensure the quality of their software products. As a system evolves and is extended with new features the test suite also typically grows as new test cases are added. To ensure software quality throughout this process the test suite is continously executed, often on a daily basis. It seems likely that newly added tests would be more likely to fail than older tests but this has not been investigated in any detail on large-scale, industrial software systems. Also it is not clear which methods should be used to conduct such an analysis. This paper proposes three main concepts that can be used to investigate aging effects in the use and failure behavior of system test cases: test case activation curves, test case hazard curves, and test case half-life. To evaluate these concepts and the type of analysis they enable we apply them on an industrial software system containing more than one million lines of code. The data sets comes from a total of 1,620 system test cases executed a total of more than half a million times over a time period of two and a half years. For the investigated system we find that system test cases stay active as they age but really do grow old; they go through an infant mortality phase with higher failure rates which then decline over time. The test case half-life is between 5 to 12 months for the two studied data sets.
Covering Pairs in Directed Acyclic Graphs
Venue: arXiv cs.DS 2013
Year: 2013

The Minimum Path Cover problem on directed acyclic graphs (DAGs) is a classical problem that provides a clear and simple mathematical formulation for several applications in different areas and that has an efficient algorithmic solution. In this paper, we study the computational complexity of two constrained variants of Minimum Path Cover motivated by the recent introduction of next-generation sequencing technologies in bioinformatics. The first problem (MinPCRP), given a DAG and a set of pairs of vertices, asks for a minimum cardinality set of paths "covering" all the vertices such that both vertices of each pair belong to the same path. For this problem, we show that, while it is NP-hard to compute if there exists a solution consisting of at most three paths, it is possible to decide in polynomial time whether a solution consisting of at most two paths exists. The second problem (MaxRPSP), given a DAG and a set of pairs of vertices, asks for a path containing the maximum number of the given pairs of vertices. We show its NP-hardness and also its W[1]-hardness when parametrized by the number of covered pairs. On the positive side, we give a fixed-parameter algorithm when the parameter is the maximum overlapping degree, a natural parameter in the bioinformatics applications of the problem.
Advances in Hyperspectral Image Classification: Earth monitoring with statistical learning methods
Venue: arXiv cs.CV 2013
Year: 2013

Hyperspectral images show similar statistical properties to natural grayscale or color photographic images. However, the classification of hyperspectral images is more challenging because of the very high dimensionality of the pixels and the small number of labeled examples typically available for learning. These peculiarities lead to particular signal processing problems, mainly characterized by indetermination and complex manifolds. The framework of statistical learning has gained popularity in the last decade. New methods have been presented to account for the spatial homogeneity of images, to include user's interaction via active learning, to take advantage of the manifold structure with semisupervised learning, to extract and encode invariances, or to adapt classifiers and image representations to unseen yet similar scenes. This tutuorial reviews the main advances for hyperspectral remote sensing image classification through illustrative examples.
Distributed Reed-Solomon Codes for Simple Multiple Access Networks
Venue: arXiv cs.IT 2013
Year: 2013

We consider a simple multiple access network in which a destination node receives information from multiple sources via a set of relay nodes. Each relay node has access to a subset of the sources, and is connected to the destination by a unit capacity link. We also assume that $z$ of the relay nodes are adversarial. We propose a computationally efficient distributed coding scheme and show that it achieves the full capacity region for up to three sources. Specifically, the relay nodes encode in a distributed fashion such that the overall codewords received at the destination are codewords from a single Reed-Solomon code.
Soft computing techniques for software effort estimation
Venue: arXiv cs.SE 2013
Year: 2013

The effort invested in a software project is probably one of the most important and most analyzed variables in recent years in the process of project management. The limitation of algorithmic effort prediction models is their inability to cope with uncertainties and imprecision surrounding software projects at the early development stage. More recently attention has turned to a variety of machine learning methods, and soft computing in particular to predict software development effort. Soft computing is a consortium of methodologies centering in fuzzy logic, artificial neural networks, and evolutionary computation. It is important, to mention here, that these methodologies are complementary and synergistic, rather than competitive. They provide in one form or another flexible information processing capability for handling real life ambiguous situations. These methodologies are currently used for reliable and accurate estimate of software development effort, which has always been a challenge for both the software industry and academia. The aim of this study is to analyze soft computing techniques in the existing models and to provide in depth review of software and project estimation techniques existing in industry and literature based on the different test datasets along with their strength and weaknesses
Real Time Data Warehouse
Venue: arXiv cs.DB 2013
Year: 2013

Data Warehouse (DW) is an essential part of Business Intelligence. DW emerged as a fast growing reporting and analysis technique in early 1980s. Today, it has almost replaced relational databases. However, with passage of time, static and historic data of DWs could not produce Real Time reporting and analysis, thus giving a way to emerge the Idea of Real Time Data Warehouse (RTDW). Although, there are problems with RTDWs, but with advancement in technology and researchers focus, RTDWs will be able to generate real time reports, analysis and forecasting.
On the Performance of Adaptive Packetized Wireless Communication Links under Jamming
Venue: arXiv cs.IT 2013
Year: 2013

We employ a game theoretic approach to formulate communication between two nodes over a wireless link in the presence of an adversary. We define a constrained, two-player, zero-sum game between a transmitter/receiver pair with adaptive transmission parameters and an adversary with average and maximum power constraints. In this model, the transmitter's goal is to maximize the achievable expected performance of the communication link, defined by a utility function, while the jammer's goal is to minimize the same utility function. Inspired by capacity/rate as a performance measure, we define a general utility function and a payoff matrix which may be applied to a variety of jamming problems. We show the existence of a threshold such that if the jammer's average power exceeds this threshold, the expected payoff of the transmitter at Nash Equilibrium (NE) is the same as the case when the jammer uses its maximum allowable power all the time. We provide analytical and numerical results for transmitter and jammer optimal strategies and a closed form expression for the expected value of the game at the NE. As a special case, we investigate the maximum achievable transmission rate of a rate-adaptive, packetized, wireless AWGN communication link under different jamming scenarios and show that randomization can significantly assist a smart jammer with limited average power.
Privacy in RFID and mobile objects
Venue: arXiv cs.CR 2013
Year: 2013

Radio Frequency Identification (RFID) is a technology aimed at eficiently identifying and tracking goods and assets. Such identification may be performed without requiring line-of-sight alignment or physical contact between the RFID tag and the RFID reader, whilst tracking is naturally achieved due to the short interrogation field of RFID readers. That is why the reduction in price of the RFID tags has been accompanied with an increasing attention paid to this technology. However, since tags are resource-constrained devices sending identification data wirelessly, designing secure and private RFID identification protocols is a challenging task. This scenario is even more complex when scalability must be met by those protocols. Assuming the existence of a lightweight, secure, private and scalable RFID identification protocol, there exist other concerns surrounding the RFID technology. Some of them arise from the technology itself, such as distance checking, but others are related to the potential of RFID systems to gather huge amount of tracking data. Publishing and mining such moving objects data is essential to improve efficiency of supervisory control, assets management and localisation, transportation, etc. However, obvious privacy threats arise if an individual can be linked with some of those published trajectories. The present dissertation contributes to the design of algorithms and protocols aimed at dealing with the issues explained above. First, we propose a set of protocols and heuristics based on a distributed architecture that improve the efficiency of the identification process without compromising privacy or security. Moreover, we present a novel distance-bounding protocol based on graphs that is extremely low-resource consuming. Finally, we present two trajectory anonymisation methods aimed at preserving the individuals' privacy when their trajectories are released.
Using CamiTK for rapid prototyping of interactive Computer Assisted Medical Intervention applications
Venue: arXiv cs.OH 2013
Year: 2013

Computer Assisted Medical Intervention (CAMI hereafter) is a complex multi-disciplinary field. CAMI research requires the collaboration of experts in several fields as diverse as medicine, computer science, mathematics, instrumentation, signal processing, mechanics, modeling, automatics, optics, etc.
Parameterized (in)approximability of subset problems
Venue: arXiv cs.CC 2013
Year: 2013

We discuss approximability and inapproximability in FPT-time for a large class of subset problems where a feasible solution $S$ is a subset of the input data and the value of $S$ is $|S|$. The class handled encompasses many well-known graph, set, or satisfiability problems such as Dominating Set, Vertex Cover, Set Cover, Independent Set, Feedback Vertex Set, etc. In a first time, we introduce the notion of intersective approximability that generalizes the one of safe approximability and show strong parameterized inapproximability results for many of the subset problems handled. Then, we study approximability of these problems with respect to the dual parameter $n-k$ where $n$ is the size of the instance and $k$ the standard parameter. More precisely, we show that under such a parameterization, many of these problems, while W[$\cdot$]-hard, admit parameterized approximation schemata.
CIDS country rankings: comparing documents and citations of USA, UK and China top researchers
Venue: arXiv cs.DL 2013
Year: 2013

This technical report presents a bibliometric analysis of the top 30 cited researchers from USA, UK and China. The analysis is based on Google Scholar data using CIDS. The researchers were identified using their email suffix: edu, uk and cn. This naïve approach was able to produce rankings consistent with the SCImago country rankings using mininal resources in a fully automated way.
Devnagari Handwritten Numeral Recognition using Geometric Features and Statistical Combination Classifier
Venue: arXiv cs.CV 2013
Year: 2013

This paper presents a Devnagari Numerical recognition method based on statistical discriminant functions. 17 geometric features based on pixel connectivity, lines, line directions, holes, image area, perimeter, eccentricity, solidity, orientation etc. are used for representing the numerals. Five discriminant functions viz. Linear, Quadratic, Diaglinear, Diagquadratic and Mahalanobis distance are used for classification. 1500 handwritten numerals are used for training. Another 1500 handwritten numerals are used for testing. Experimental results show that Linear, Quadratic and Mahalanobis discriminant functions provide better results. Results of these three Discriminants are fed to a majority voting type Combination classifier. It is found that Combination classifier offers better results over individual classifiers.
Union of Random Minkowski Sums and Network Vulnerability Analysis
Venue: arXiv cs.CG 2013
Year: 2013

Let $\mathcal{C}=\{C_1,\ldots,C_n\}$ be a set of $n$ pairwise-disjoint convex sets of constant description complexity, and let $π$ be a probability density function (pdf for short) over the non-negative reals. For each $i$, let $K_i$ be the Minkowski sum of $C_i$ with a disk of radius $r_i$, where each $r_i$ is a random non-negative number drawn independently from the distribution determined by $π$. We show that the expected complexity of the union of $K_1, \ldots, K_n$ is $O(n^{1+\varepsilon})$ for any $\varepsilon > 0$; here the constant of proportionality depends on $\varepsilon$ and on the description complexity of the sets in $\mathcal{C}$, but not on $π$. If each $C_i$ is a convex polygon with at most $s$ vertices, then we show that the expected complexity of the union is $O(s^2n\log n)$. Our bounds hold in the stronger model in which we are given an arbitrary multi-set $R=\{r_1,\ldots,r_n\}$ of expansion radii, each a non-negative real number. We assign them to the members of $\mathcal{C}$ by a random permutation, where all permutations are equally likely to be chosen; the expectations are now with respect to these permutations. We also present an application of our results to a problem that arises in analyzing the vulnerability of a network to a physical attack. %
Short $\mathsf{Res}^*(\mathsf{polylog})$ refutations if and only if narrow $\mathsf{Res}$ refutations
Venue: arXiv cs.CC 2013
Year: 2013

In this note we show that any $k$-CNF which can be refuted by a quasi-polynomial $\mathsf{Res}^*(\mathsf{polylog})$ refutation has a "narrow" refutation in $\mathsf{Res}$ (i.e., of poly-logarithmic width). We also show the converse implication: a narrow Resolution refutation can be simulated by a short $\mathsf{Res}^*(\mathsf{polylog})$ refutation. The author does not claim priority on this result. The technical part of this note bears similarity with the relation between $d$-depth Frege refutations and tree-like $d+1$-depth Frege refutations outlined in (Krajíček 1994, Journal of Symbolic Logic 59, 73). Part of it had already been specialized to $\mathsf{Res}$ and $\mathsf{Res}(k)$ in (Esteban et al. 2004, Theor. Comput. Sci. 321, 347).
Determination, Calculation and Representation of the Upper and Lower Sealing Zones During Virtual Stenting of Aneurysms
Venue: arXiv cs.CV 2013
Year: 2013

In this contribution, a novel method for stent simulation in preoperative computed tomography angiography (CTA) acquisitions of patients is presented where the sealing zones are automatically calculated and visualized. The method is eligible for non-bifurcated and bifurcated stents (Y-stents). Results of the proposed stent simulation with an automatic calculation of the sealing zones for specific diseases (abdominal aortic aneurysms (AAA), thoracic aortic aneurysms (TAA), iliac aneurysms) are presented. The contribution is organized as follows. Section 2 presents the proposed approach. In Section 3, experimental results are discussed. Section 4 concludes the contribution and outlines areas for future work.
U.S. academic libraries: understanding their web presence and their relationship with economic indicators
Venue: arXiv cs.DL 2013
Year: 2013

The main goal of this research is to analyze the web structure and performance of units and services belonging to U.S. academic libraries in order to check their suitability for webometric studies. Our objectives include studying their possible correlation with economic data and assessing their use for complementary evaluation purposes. We conducted a survey of library homepages, institutional repositories, digital collections, and online catalogs (a total of 374 URLs) belonging to the 100 U.S. universities with the highest total expenditures in academic libraries according to data provided by the National Center for Education Statistics (NCES). Several data points were taken and analyzed, including web variables (page count, external links, and visits) and economic variables (total expenditures, expenditures on printed and electronic books, and physical visits). The results indicate that the variety of URL syntaxes is wide, diverse and complex, which produces a misrepresentation of academic library web resources and reduces the accuracy of web analysis. On the other hand, institutional and web data indicators are not highly correlated. Better results are obtained by correlating total library expenditures with URL mentions measured by Google (r= 0.546) and visits measured by Compete (r= 0.573), respectively. Because correlation values obtained are not highly significant, we estimate such correlations will increase if users can avoid linkage problems (due to the complexity of URLs) and gain direct access to log files (for more accurate data about visits).