OpenRaiser/Intern-Atlas huggingface dataset:
When and By How Much Can Helper Node Selection Improve Regenerating Codes?
Venue: arXiv cs.IT 2014
Year: 2014

Regenerating codes (RCs) can significantly reduce the repair-bandwidth of distributed storage networks. Initially, the analysis of RCs was based on the assumption that during the repair process, the newcomer does not distinguish (among all surviving nodes) which nodes to access, i.e., the newcomer is oblivious to the set of helpers being used. Such a scheme is termed the blind repair (BR) scheme. Nonetheless, it is intuitive in practice that the newcomer should choose to access only those "good" helpers. In this paper, a new characterization of the effect of choosing the helper nodes in terms of the storage-bandwidth tradeoff is given. Specifically, answers to the following fundamental questions are given: Under what conditions does proactively choosing the helper nodes improve the storage-bandwidth tradeoff? Can this improvement be analytically quantified? This paper answers the former question by providing a necessary and sufficient condition under which optimally choosing good helpers strictly improves the storage-bandwidth tradeoff. To answer the latter question, a low-complexity helper selection solution, termed the family repair (FR) scheme, is proposed and the corresponding storage/repair-bandwidth curve is characterized. For example, consider a distributed storage network with 60 total number of nodes and the network is resilient against 50 node failures. If the number of helper nodes is 10, then the FR scheme and its variant demonstrate 27% reduction in the repair-bandwidth when compared to the BR solution. This paper also proves that under some design parameters, the FR scheme is indeed optimal among all helper selection schemes. An explicit construction of an exact-repair code is also proposed that can achieve the minimum-bandwidth-regenerating point of the FR scheme. The new exact-repair code can be viewed as a generalization of the existing fractional repetition code.
XTribe: a web-based social computation platform
Venue: arXiv cs.CY 2014
Year: 2014

In the last few years the Web has progressively acquired the status of an infrastructure for social computation that allows researchers to coordinate the cognitive abilities of human agents in on-line communities so to steer the collective user activity towards predefined goals. This general trend is also triggering the adoption of web-games as a very interesting laboratory to run experiments in the social sciences and whenever the contribution of human beings is crucially required for research purposes. Nowadays, while the number of on-line users has been steadily growing, there is still a need of systematization in the approach to the web as a laboratory. In this paper we present Experimental Tribe (XTribe in short), a novel general purpose web-based platform for web-gaming and social computation. Ready to use and already operational, XTribe aims at drastically reducing the effort required to develop and run web experiments. XTribe has been designed to speed up the implementation of those general aspects of web experiments that are independent of the specific experiment content. For example, XTribe takes care of user management by handling their registration and profiles and in case of multi-player games, it provides the necessary user grouping functionalities. XTribe also provides communication facilities to easily achieve both bidirectional and asynchronous communication. From a practical point of view, researchers are left with the only task of designing and implementing the game interface and logic of their experiment, on which they maintain full control. Moreover, XTribe acts as a repository of different scientific experiments, thus realizing a sort of showcase that stimulates users' curiosity, enhances their participation, and helps researchers in recruiting volunteers.
Semantic Similarity Measures Applied to an Ontology for Human-Like Interaction
Venue: arXiv cs.AI 2014
Year: 2014

The focus of this paper is the calculation of similarity between two concepts from an ontology for a Human-Like Interaction system. In order to facilitate this calculation, a similarity function is proposed based on five dimensions (sort, compositional, essential, restrictive and descriptive) constituting the structure of ontological knowledge. The paper includes a proposal for computing a similarity function for each dimension of knowledge. Later on, the similarity values obtained are weighted and aggregated to obtain a global similarity measure. In order to calculate those weights associated to each dimension, four training methods have been proposed. The training methods differ in the element to fit: the user, concepts or pairs of concepts, and a hybrid approach. For evaluating the proposal, the knowledge base was fed from WordNet and extended by using a knowledge editing toolkit (Cognos). The evaluation of the proposal is carried out through the comparison of system responses with those given by human test subjects, both providing a measure of the soundness of the procedure and revealing ways in which the proposal may be improved.
On the Capacity of Memoryless Adversary
Venue: arXiv cs.IT 2014
Year: 2014

In this paper, we study a model of communication under adversarial noise. In this model, the adversary makes online decisions on whether to corrupt a transmitted bit based on only the value of that bit. Like the usual binary symmetric channel of information theory or the fully adversarial channel of combinatorial coding theory, the adversary can, with high probability, introduce at most a given fraction of error. It is shown that, the capacity (maximum rate of reliable information transfer) of such memoryless adversary is strictly below that of the binary symmetric channel. We give new upper bound on the capacity of such channel -- the tightness of this upper bound remains an open question. The main component of our proof is the careful examination of error-correcting properties of a code with skewed distance distribution.
Computation Tree Logic Model Checking Based on Possibility Measures
Venue: arXiv cs.LO 2014
Year: 2014

In order to deal with the systematic verification with uncertain infromation in possibility theory, Li and Li \cite{li12} introduced model checking of linear-time properties in which the uncertainty is modeled by possibility measures. Xue, Lei and Li \cite{Xue09} defined computation tree logic (CTL) based on possibility measures, which is called possibilistic CTL (PoCTL). This paper is a continuation of the above work. First, we study the expressiveness of PoCTL. Unlike probabilistic CTL, it is shown that PoCTL (in particular, qualitative PoCTL) is more powerful than CTL with respect to their expressiveness. The equivalent expressions of basic CTL formulae using qualitative PoCTL formulae are presented in detail. Some PoCTL formulae that can not be expressed by any CTL formulae are presented. In particular, some qualitative properties of repeated reachability and persistence are expressed using PoCTL formulae. Next, adapting CTL model-checking algorithm, a method to solve the PoCTL model-checking problem and its time complexity are discussed in detail. Finally, an example is given to illustrate the PoCTL model-checking method.
Parallel Telescoping and Parameterized Picard--Vessiot Theory
Venue: arXiv cs.SC 2014
Year: 2014

Parallel telescoping is a natural generalization of differential creative-telescoping for single integrals to line integrals. It computes a linear ordinary differential operator $L$, called a parallel telescoper, for several multivariate functions, such that the applications of $L$ to the functions yield antiderivatives of a single function. We present a necessary and sufficient condition guaranteeing the existence of parallel telescopers for differentially finite functions, and develop an algorithm to compute minimal ones for compatible hyperexponential functions. Besides computing annihilators of parametric line integrals, we use the parallel telescoping for determining Galois groups of parameterized partial differential systems of first order.
Evolving Accuracy: A Genetic Algorithm to Improve Election Night Forecasts
Venue: arXiv cs.NE 2014
Year: 2014

In this paper, we apply genetic algorithms to the field of electoral studies. Forecasting election results is one of the most exciting and demanding tasks in the area of market research, especially due to the fact that decisions have to be made within seconds on live television. We show that the proposed method outperforms currently applied approaches and thereby provide an argument to tighten the intersection between computer science and social science, especially political science, further. We scrutinize the performance of our algorithm's runtime behavior to evaluate its applicability in the field. Numerical results with real data from a local election in the Austrian province of Styria from 2010 substantiate the applicability of the proposed approach.
Random-bit optimal uniform sampling for rooted planar trees with given sequence of degrees and Applications
Venue: arXiv cs.DM 2014
Year: 2014

In this paper, we redesign and simplify an algorithm due to Remy et al. for the generation of rooted planar trees that satisfies a given partition of degrees. This new version is now optimal in terms of random bit complexity, up to a multiplicative constant. We then apply a natural process "simulate-guess-and-proof" to analyze the height of a random Motzkin in function of its frequency of unary nodes. When the number of unary nodes dominates, we prove some unconventional height phenomenon (i.e. outside the universal square root behaviour.)
A Novel Admission Control Model in Cloud Computing
Venue: arXiv cs.NI 2014
Year: 2014

With the rapid development of Cloud computing technologies and wide adopt of Cloud services and applications, QoS provisioning in Clouds becomes an important research topic. In this paper, we propose an admission control mechanism for Cloud computing. In particular we consider the high volume of simultaneous requests for Cloud services and develop admission control for aggregated traffic flows to address this challenge. By employ network calculus, we determine effective bandwidth for aggregate flow, which is used for making admission control decision. In order to improve network resource allocation while achieving Cloud service QoS, we investigate the relationship between effective bandwidth and equivalent capacity. We have also conducted extensive experiments to evaluate performance of the proposed admission control mechanism.
A Model for Privacy-enhanced Federated Identity Management
Venue: arXiv cs.CR 2014
Year: 2014

Identity federations operating in a business or consumer context need to prevent the collection of user data across trust service providers for legal and business case reasons. Legal reasons are given by data protection legislation. Other reasons include business owners becoming increasingly aware of confidentiality risks that go beyond traditional information security, e.g., the numbers of authentications to an EDI service might provide insights into the volume of invoices, from which one could derive insider information. This paper proposes extended technical controls supporting three privacy requirements: a) Limit d Linkability: Two service providers cannot link data related to a user without the help of a third party, using neither an identifier nor other identifying attributes like email addresses or payment data; b) Limited Observability: An identity provider cannot trace which services a user is using without the help of a third party; c) Non-Disclosure: Attributes provided to the service provider by an attribute provider are not disclosed to the identity provider or an intermediate service broker. Using a hub-and-spoke federation style following the privacy-by-design principle, this reference architecture addresses the privacy controls mentioned above.
Generalization of the PageRank Model
Venue: arXiv cs.SI 2014
Year: 2014

This paper develops a generalization of the PageRank model of page centralities in the global webgraph of hyperlinks. The webgraph of adjacencies is generalized to a valued directed graph, and the scalar dampening coefficient for walks through the graph is relaxed to allow for heterogeneous values. A visitation count approach may be employed to apply the more general model, based on the number of visits to a page and the page's proportionate allocations of these visits to other nodes of the webgraph.
Generalized Bhattacharyya and Chernoff upper bounds on Bayes error using quasi-arithmetic means
Venue: arXiv cs.CV 2014
Year: 2014

Bayesian classification labels observations based on given prior information, namely class-a priori and class-conditional probabilities. Bayes' risk is the minimum expected classification cost that is achieved by the Bayes' test, the optimal decision rule. When no cost incurs for correct classification and unit cost is charged for misclassification, Bayes' test reduces to the maximum a posteriori decision rule, and Bayes risk simplifies to Bayes' error, the probability of error. Since calculating this probability of error is often intractable, several techniques have been devised to bound it with closed-form formula, introducing thereby measures of similarity and divergence between distributions like the Bhattacharyya coefficient and its associated Bhattacharyya distance. The Bhattacharyya upper bound can further be tightened using the Chernoff information that relies on the notion of best error exponent. In this paper, we first express Bayes' risk using the total variation distance on scaled distributions. We then elucidate and extend the Bhattacharyya and the Chernoff upper bound mechanisms using generalized weighted means. We provide as a byproduct novel notions of statistical divergences and affinity coefficients. We illustrate our technique by deriving new upper bounds for the univariate Cauchy and the multivariate $t$-distributions, and show experimentally that those bounds are not too distant to the computationally intractable Bayes' error.
Classification of IDS Alerts with Data Mining Techniques
Venue: arXiv cs.CR 2014
Year: 2014

A data mining technique to reduce the amount of false alerts within an IDS system is proposed. The new technique achieves an accuracy of 99% compared to 97% by the current systems.
Spoiled Onions: Exposing Malicious Tor Exit Relays
Venue: arXiv cs.CR 2014
Year: 2014

Several hundred Tor exit relays together push more than 1 GiB/s of network traffic. However, it is easy for exit relays to snoop and tamper with anonymised network traffic and as all relays are run by independent volunteers, not all of them are innocuous. In this paper, we seek to expose malicious exit relays and document their actions. First, we monitored the Tor network after developing a fast and modular exit relay scanner. We implemented several scanning modules for detecting common attacks and used them to probe all exit relays over a period of four months. We discovered numerous malicious exit relays engaging in different attacks. To reduce the attack surface users are exposed to, we further discuss the design and implementation of a browser extension patch which fetches and compares suspicious X.509 certificates over independent Tor circuits. Our work makes it possible to continuously monitor Tor exit relays. We are able to detect and thwart many man-in-the-middle attacks which makes the network safer for its users. All our code is available under a free license.
On the Cartesian Skeleton and the Factorization of the Strong Product of Digraphs
Venue: arXiv cs.DM 2014
Year: 2014

The three standard products (the Cartesian, the direct and the strong product) of undirected graphs have been wellinvestigated, unique prime factor decomposition (PFD) are known and polynomial time algorithms have been established for determining the prime factors. For directed graphs, unique PFD results with respect to the standard products are known. However, there is still a lack of algorithms, that computes the PFD of directed graphs with respect to the direct and the strong product in general. In this contribution, we focus on the algorithmic aspects for determining the PFD of directed graphs with respect to the strong product. Essential for computing the prime factors is the construction of a so-called Cartesian skeleton. This article introduces the notion of the Cartesian skeleton of directed graphs as a generalization of the Cartesian skeleton of undirected graphs. We provide new, fast and transparent algorithms for its construction. Moreover, we present a first polynomial time algorithm for determining the PFD with respect to the strong product of arbitrary connected digraphs.
WaterFowl, a Compact, Self-indexed RDF Store with Inference-enabled Dictionaries
Venue: arXiv cs.DB 2014
Year: 2014

In this paper, we present a novel approach -- called WaterFowl -- for the storage of RDF triples that addresses some key issues in the contexts of big data and the Semantic Web. The architecture of our prototype, largely based on the use of succinct data structures, enables the representation of triples in a self-indexed, compact manner without requiring decompression at query answering time. Moreover, it is adapted to efficiently support RDF and RDFS entailment regimes thanks to an optimized encoding of ontology concepts and properties that does not require a complete inference materialization or extensive query rewriting algorithms. This approach implies to make a distinction between the terminological and the assertional components of the knowledge base early in the process of data preparation, i.e., preprocessing the data before storing it in our structures. The paper describes the complete architecture of this system and presents some preliminary results obtained from evaluations conducted on our first prototype.
Study of Efficient Technique Based On 2D Tsallis Entropy For Image Thresholding
Venue: arXiv cs.CV 2014
Year: 2014

Thresholding is an important task in image processing. It is a main tool in pattern recognition, image segmentation, edge detection and scene analysis. In this paper, we present a new thresholding technique based on two-dimensional Tsallis entropy. The two-dimensional Tsallis entropy was obtained from the twodimensional histogram which was determined by using the gray value of the pixels and the local average gray value of the pixels, the work it was applied a generalized entropy formalism that represents a recent development in statistical mechanics. The effectiveness of the proposed method is demonstrated by using examples from the real-world and synthetic images. The performance evaluation of the proposed technique in terms of the quality of the thresholded images are presented. Experimental results demonstrate that the proposed method achieve better result than the Shannon method.
Identifying Benefits and risks associated with utilizing cloud computing
Venue: arXiv cs.DC 2014
Year: 2014

Cloud computing is an emerging computing model where IT and computing operations are delivered as services in highly scalable and cost effective manner. Recently, embarking this new model in business has become popular. Companies in diverse sectors intend to leverage cloud computing architecture, platforms and applications in order to gain higher competitive advantages. Likewise other models, cloud computing brought advantages to attract business but meanwhile fostering cloud has led to some risks, which can cause major impacts if business does not plan for mitigation. This paper surveys the advantages of cloud computing and in contrast the risks associated using them. Finally we conclude that a well-defined risk management program that focused on cloud computing is an essential part of gaining value from benefits of cloud computing.
A Genetic Algorithm based Approach for Test Data Generation in Basis Path Testing
Venue: arXiv cs.SE 2014
Year: 2014

Software Testing is a process to identify the quality and reliability of software, which can be achieved through the help of proper test data. However, doing this manually is a difficult task due to the presence of number of predicate nodes in the module. So, this leads towards a problem of NP-complete. Therefore some intelligence-based search algorithms have to be used to generate test data. In this paper, we use a soft computing based approach, genetic algorithm to generate test data based on the set of basis paths. This paper combines the characteristics of genetic algorithm with test data, making use of the merits of respective global and local optimization capability to improve the generation capacity of test data. This automated process of generating test data optimally helps in reducing the test effort and time of a tester. Finally, the proposed approach is applied for ATM withdrawal task. Experimental results show that genetic algorithm was able to generate suitable test data based on a fitness value and avoid redundant data by optimization.
Inequalities for the Bayes Risk
Venue: arXiv cs.IT 2014
Year: 2014

Several inequalities are presented which, in part, generalize inequalities by Weinstein and Weiss, giving rise to new lower bounds for the Bayes risk under squared error loss.
An Integrated Approach for Identifying Relevant Factors Influencing Software Development Productivity
Venue: arXiv cs.SE 2014
Year: 2014

Managing software development productivity and effort are key issues in software organizations. Identifying the most relevant factors influencing project performance is essential for implementing business strategies by selecting and adjusting proper improvement activities. There is, however, a large number of potential influencing factors. This paper proposes a novel approach for identifying the most relevant factors influencing software development productivity. The method elicits relevant factors by integrating data analysis and expert judgment approaches by means of a multi-criteria decision support technique. Empirical evaluation of the method in an industrial context has indicated that it delivers a different set of factors compared to individual data- and expert-based factor selection methods. Moreover, application of the integrated method significantly improves the performance of effort estimation in terms of accuracy and precision. Finally, the study did not replicate the observation of similar investigations regarding improved estimation performance on the factor sets reduced by a data-based selection method.
A Microkernel Architecture for Constraint Programming
Venue: arXiv cs.AI 2014
Year: 2014

This paper presents a microkernel architecture for constraint programming organized around a number of small number of core functionalities and minimal interfaces. The architecture contrasts with the monolithic nature of many implementations. Experimental results indicate that the software engineering benefits are not incompatible with runtime efficiency.
Software Licensing in the Cloud Age
Venue: arXiv cs.CY 2014
Year: 2014

Cloud computing represents a major shift in information systems architecture, combining both new deployment models and new business models. Rapid provisioning, elastic scaling, and metered usage are essential characteristics of cloud services, and they require cloud resources with these same characteristics. When cloud services depend on commercial software, the licenses for that software become another resource to be managed by the cloud. This paper examines common licensing models, including open source, and how well they function in a cloud services model. It discusses creative, new, cloud-centric licensing models and how they allow providers to preserve and expand their revenue streams as their partners and customers transition to the cloud. The paper concludes by identifying the next steps to achieve standardized, cloud-friendly licensing models.
STABLAB Documentation for KdV : Numerical proof of stability of roll waves in the small-amplitude limit for inclined thin film flow
Venue: arXiv cs.MS 2014
Year: 2014

We document the MATLAB code used in the following study: Numerical proof of stability of roll waves in the small-amplitude limit for inclined thin film flow.