OpenRaiser/Intern-Atlas huggingface dataset:
Mining Block I/O Traces for Cache Preloading with Sparse Temporal Non-parametric Mixture of Multivariate Poisson
Venue: arXiv cs.OS 2014
Year: 2014

Existing caching strategies, in the storage domain, though well suited to exploit short range spatio-temporal patterns, are unable to leverage long-range motifs for improving hitrates. Motivated by this, we investigate novel Bayesian non-parametric modeling(BNP) techniques for count vectors, to capture long range correlations for cache preloading, by mining Block I/O traces. Such traces comprise of a sequence of memory accesses that can be aggregated into high-dimensional sparse correlated count vector sequences. While there are several state of the art BNP algorithms for clustering and their temporal extensions for prediction, there has been no work on exploring these for correlated count vectors. Our first contribution addresses this gap by proposing a DP based mixture model of Multivariate Poisson (DP-MMVP) and its temporal extension(HMM-DP-MMVP) that captures the full covariance structure of multivariate count data. However, modeling full covariance structure for count vectors is computationally expensive, particularly for high dimensional data. Hence, we exploit sparsity in our count vectors, and as our main contribution, introduce the Sparse DP mixture of multivariate Poisson(Sparse-DP-MMVP), generalizing our DP-MMVP mixture model, also leading to more efficient inference. We then discuss a temporal extension to our model for cache preloading. We take the first step towards mining historical data, to capture long range patterns in storage traces for cache preloading. Experimentally, we show a dramatic improvement in hitrates on benchmark traces and lay the groundwork for further research in storage domain to reduce latencies using data mining techniques to capture long range motifs.
Stochastic Geometry Modeling and Analysis of Multi-Tier Millimeter Wave Cellular Networks
Venue: arXiv cs.IT 2014
Year: 2014

In this paper, a new mathematical framework to the analysis of millimeter wave cellular networks is introduced. Its peculiarity lies in considering realistic path-loss and blockage models, which are derived from recently reported experimental data. The path-loss model accounts for different distributions of line-of-sight and non-line-of-sight propagation conditions and the blockage model includes an outage state that provides a better representation of the outage possibilities of millimeter wave communications. By modeling the locations of the base stations as points of a Poisson point process and by relying on a noise-limited approximation for typical millimeter wave network deployments, simple and exact integral as well as approximated and closed-form formulas for computing the coverage probability and the average rate are obtained. With the aid of Monte Carlo simulations, the noise-limited approximation is shown to be sufficiently accurate for typical network densities. The proposed mathematical framework is applicable to cell association criteria based on the smallest path-loss and on the highest received power. It accounts for beamforming alignment errors and for multi-tier cellular network deployments. Numerical results confirm that sufficiently dense millimeter wave cellular networks are capable of outperforming micro wave cellular networks, both in terms of coverage probability and average rate.
Does A Paper Being Featured on The Cover of A Journal Guarantee More Attention and Greater Impact?
Venue: arXiv cs.DL 2014
Year: 2014

Paper featured on the cover of a journal has more visibility in an issue compared with other ordinary articles for both printed and electronic journal. Does this kind of visibility guarantee more attention and greater impact of its associated content than the non-cover papers? In this research, usage and citation data of 60 issues of PLOS Biology from 2006 to 2010 are analyzed to compare the attention and scholarly impact between cover and non-cover paper. Our empirical study confirms that, in most cases, the group difference between cover and non-cover paper is not significant for attention or impact. Cover paper is not the best one, nor at the upper level in one issue considering the attention or the citation impact. Having a paper featured on the cover of a journal may be a source of pride to researchers, many institutions and researchers would even release news about it. However, a paper being featured on the cover of a journal doesn't guarantee more attention and greater impact.
Training Beam Sequence Design for Millimeter-Wave MIMO Systems: A POMDP Framework
Venue: arXiv cs.IT 2014
Year: 2014

In this paper, adaptive training beam sequence design for efficient channel estimation in large millimeter-wave(mmWave) multiple-input multiple-output (MIMO) channels is considered. By exploiting the sparsity in large mmWave MIMO channels and imposing a Markovian random walk assumption on the movement of the receiver and reflection clusters, the adaptive training beam sequence design and channel estimation problem is formulated as a partially observableMarkov decision process (POMDP) problem that finds non-zero bins in a two-dimensional grid. Under the proposed POMDP framework, optimal and suboptimal adaptive training beam sequence design policies are derived. Furthermore, a very fast suboptimal greedy algorithm is developed based on a newly proposed reduced sufficient statistic to make the computational complexity of the proposed algorithm low to a level for practical implementation. Numerical results are provided to evaluate the performance of the proposed training beam design method. Numerical results show that the proposed training beam sequence design algorithms yield good performance.
Thompson sampling with the online bootstrap
Venue: arXiv cs.LG 2014
Year: 2014

Thompson sampling provides a solution to bandit problems in which new observations are allocated to arms with the posterior probability that an arm is optimal. While sometimes easy to implement and asymptotically optimal, Thompson sampling can be computationally demanding in large scale bandit problems, and its performance is dependent on the model fit to the observed data. We introduce bootstrap Thompson sampling (BTS), a heuristic method for solving bandit problems which modifies Thompson sampling by replacing the posterior distribution used in Thompson sampling by a bootstrap distribution. We first explain BTS and show that the performance of BTS is competitive to Thompson sampling in the well-studied Bernoulli bandit case. Subsequently, we detail why BTS using the online bootstrap is more scalable than regular Thompson sampling, and we show through simulation that BTS is more robust to a misspecified error distribution. BTS is an appealing modification of Thompson sampling, especially when samples from the posterior are otherwise not available or are costly.
An upper bound on the k-modem illumination problem
Venue: arXiv cs.CG 2014
Year: 2014

A variation on the classical polygon illumination problem was introduced in [Aichholzer et. al. EuroCG'09]. In this variant light sources are replaced by wireless devices called k-modems, which can penetrate a fixed number k, of "walls". A point in the interior of a polygon is "illuminated" by a k-modem if the line segment joining them intersects at most k edges of the polygon. It is easy to construct polygons of n vertices where the number of k-modems required to illuminate all interior points is Omega(n/k). However, no non-trivial upper bound is known. In this paper we prove that the number of k-modems required to illuminate any polygon of n vertices is at most O(n/k). For the cases of illuminating an orthogonal polygon or a set of disjoint orthogonal segments, we give a tighter bound of 6n/k + 1. Moreover, we present an O(n log n) time algorithm to achieve this bound.
Analysis of corporate environmental reports using statistical techniques and data mining
Venue: arXiv cs.AI 2014
Year: 2014

Measuring the effectiveness of corporate environmental reports, it being highly qualitative and less regulated, is often considered as a daunting task. The task becomes more complex if comparisons are to be performed. This study is undertaken to overcome the physical verification problems by implementing data mining technique. It further explores on the effectiveness by performing exploratory analysis and structural equation model to bring out the significant linkages between the selected 10 variables. Samples of five hundred and thirty nine reports across various countries are used from an international directory to perform the statistical analysis like: One way ANOVA (Analysis of Variance), MDA (Multivariate Discriminant Analysis) and SEM (Structural Equation Modeling). The results indicate the significant differences among the various types of industries in their environmental reporting, and the exploratory factors like stakeholder, organization strategy and industrial oriented factors, proved significant. The major accomplishment is that the findings correlate with the conceptual frame work of GRI.
Consistent Weighted Sampling Made Fast, Small, and Easy
Venue: arXiv cs.DS 2014
Year: 2014

Document sketching using Jaccard similarity has been a workable effective technique in reducing near-duplicates in Web page and image search results, and has also proven useful in file system synchronization, compression and learning applications. Min-wise sampling can be used to derive an unbiased estimator for Jaccard similarity and taking a few hundred independent consistent samples leads to compact sketches which provide good estimates of pairwise-similarity. Subsequent works extended this technique to weighted sets and show how to produce samples with only a constant number of hash evaluations for any element, independent of its weight. Another improvement by Li et al. shows how to speedup sketch computations by computing many (near-)independent samples in one shot. Unfortunately this latter improvement works only for the unweighted case. In this paper we give a simple, fast and accurate procedure which reduces weighted sets to unweighted sets with small impact on the Jaccard similarity. This leads to compact sketches consisting of many (near-)independent weighted samples which can be computed with just a small constant number of hash function evaluations per weighted element. The size of the produced unweighted set is furthermore a tunable parameter which enables us to run the unweighted scheme of Li et al. in the regime where it is most efficient. Even when the sets involved are unweighted, our approach gives a simple solution to the densification problem that other works attempted to address. Unlike previously known schemes, ours does not result in an unbiased estimator. However, we prove that the bias introduced by our reduction is negligible and that the standard deviation is comparable to the unweighted case. We also empirically evaluate our scheme and show that it gives significant gains in computational efficiency, without any measurable loss in accuracy.
Mobile Learning Culture and Effects in Higher Education
Venue: arXiv cs.CY 2014
Year: 2014

Mobile learning through wireless enabled laptops (say, within a university campus) can make use of the learning management system that is already available through internet or intranet. Without restrictions within the four walls of computer labs or library, students can now access the learning resources anywhere in the campus where wireless access points or hotspots are located. We briefly investigate on the mobile learning benefits and eventually an analysis of the student perceptions on mobile learning is presented through a survey, to validate the m-learning benefits.
On the Feasibility and Implications of Self-Contained Search Engines in the Browser
Venue: arXiv cs.IR 2014
Year: 2014

JavaScript engines inside modern browsers are capable of running sophisticated multi-player games, rendering impressive 3D scenes, and supporting complex, interactive visualizations. Can this processing power be harnessed for information retrieval? This paper explores the feasibility of building a JavaScript search engine that runs completely self-contained on the client side within the browser---this includes building the inverted index, gathering terms statistics for scoring, and performing query evaluation. The design takes advantage of the IndexDB API, which is implemented by the LevelDB key-value store inside Google's Chrome browser. Experiments show that although the performance of the JavaScript prototype falls far short of the open-source Lucene search engine, it is sufficiently responsive for interactive applications. This feasibility demonstration opens the door to interesting applications in offline and private search across multiple platforms as well as hybrid split-execution architectures whereby clients and servers collaboratively perform query evaluation. One possible future scenario is the rise of an online search marketplace in which commercial search engine companies and individual users participate as rational economic actors, balancing privacy, resource usage, latency, and other factors based on customizable utility profiles.
Fast detection of cycles in timed automata
Venue: arXiv cs.LO 2014
Year: 2014

We propose a new efficient algorithm for detecting if a cycle in a timed automaton can be iterated infinitely often. Existing methods for this problem have a complexity which is exponential in the number of clocks. Our method is polynomial: it essentially does a logarithmic number of zone canonicalizations. This method can be incorporated in algorithms for verifying Büchi properties on timed automata. We report on some experiments that show a significant reduction in search space when our iteratability test is used.
TiQuant: Software for tissue analysis, quantification and surface reconstruction
Venue: arXiv cs.CE 2014
Year: 2014

Motivation: TiQuant is a modular software tool for efficient quantification of biological tissues based on volume data obtained by biomedical image modalities. It includes a number of versatile image and volume processing chains tailored to the analysis of different tissue types which have been experimentally verified. TiQuant implements a novel method for the reconstruction of three-dimensional surfaces of biological systems, data that often cannot be obtained experimentally but which is of utmost importance for tissue modelling in systems biology. Availability: TiQuant is freely available for non-commercial use at msysbio.com/tiquant. Windows, OSX and Linux are supported.
Identification Codes to Identify Multiple Objects
Venue: arXiv cs.IT 2014
Year: 2014

In the case of ordinary identification coding, a code is devised to identify a single object among $N$ objects. But, in this paper, we consider an identification coding problem to identify $K$ objects at once among $N$ objects in the both cases that $K$ objects are ranked or not ranked. By combining Kurosawa-Yoshida scheme with Moulin-Koetter scheme, an efficient identification coding scheme is proposed, which can attain high coding rate and error exponents compared with the case that an ordinary identification code is used $K$ times. Furthermore, the achievable triplet of rate and error exponents of type I and type II decoding error probabilities are derived for the proposed coding scheme.
Applications of different metaheuristic techniques for finding optimal tst order during integration testing of object oriented systems and their comparative study
Venue: arXiv cs.SE 2014
Year: 2014

In recent past, a number of researchers have proposed genetic algorithm (GA) based strategies for finding optimal test order while minimizing the stub complexity during integration testing. Even though, metaheuristic algorithms have a wide variety of use in various medium to large size optimization problems [21], their application to solve the class integration test order (CITO) problem [12] has not been investigated. In this research paper, we propose to find a solution to CITO problem by the use of a GA based approach. We have proposed a class dependency graph (CDG) to model dependencies namely, association, aggregation, composition and inheritance between classes of unified modeling language (UML) class diagram. In our approach, weights are assigned to the edges connecting nodes of CDG and then these weights are used to model the cost of stubbing. Finally, we compare and discuss the empirical results of applying our approach with existing graph based and metaheuristic techniques to the CITO problem and highlight the relative merits and demerits of the various techniques.
Arabic Language Text Classification Using Dependency Syntax-Based Feature Selection
Venue: arXiv cs.CL 2014
Year: 2014

We study the performance of Arabic text classification combining various techniques: (a) tfidf vs. dependency syntax, for feature selection and weighting; (b) class association rules vs. support vector machines, for classification. The Arabic text is used in two forms: rootified and lightly stemmed. The results we obtain show that lightly stemmed text leads to better performance than rootified text; that class association rules are better suited for small feature sets obtained by dependency syntax constraints; and, finally, that support vector machines are better suited for large feature sets based on morphological feature selection criteria.
Delay Optimal Secrecy in Two-Relay Network
Venue: arXiv cs.IT 2014
Year: 2014

We consider a two-relay network in which a source aims to communicate a confidential message to a destination while keeping the message secret from the relay nodes. In the first hop, the channels from the source to the relays are assumed to be block-fading and the channel states change arbitrarily -possibly non-stationary and non-ergodic- across blocks. When the relay feedback on the states of the source-to-relay channels is available on the source with no delay, we provide an encoding strategy to achieve the optimal delay. We next consider the case in which there is one-block delayed relay feedback on the states of the source-to-relay channels. We show that for a set of channel state sequences, the optimal delay with one-block delayed feedback differs from the optimal delay with no-delayed feedback at most one block.
Type-Directed Compilation for Fault-Tolerant Non-Interference
Venue: arXiv cs.CR 2014
Year: 2014

Environmental noise (e.g.heat, ionized particles, etc.) causes transient faults in hardware, which lead to corruption of stored values. Mission-critical devices require such faults to be mitigated by fault-tolerance --- a combination of techniques that aim at preserving the functional behaviour of a system despite the disruptive effects of transient faults. Fault-tolerance typically has a high deployment cost -- special hardware might be required to implement it -- and provides weak statistical guarantees. It is also based on the assumption that faults are rare. In this paper, we consider scenarios where security, rather than functional correctness, is the main asset to be protected. Our contribution is twofold. Firstly, we develop a theory for expressing confidentiality of data in the presence of transient faults. We show that the natural probabilistic definition of security in the presence of faults can be captured by a possibilistic definition. Furthermore, the possibilistic definition is implied by a known bisimulation-based property, called Strong Security. Secondly, we illustrate the utility of these results for a simple RISC architecture for which only the code memory and program counter are assumed fault-tolerant. We present a type-directed compilation scheme that produces RISC code from a higher-level language for which Strong Security holds --- i.e. well-typed programs compile to RISC code which is secure despite transient faults. In contrast with fault-tolerance solutions, our technique assumes relatively little special hardware, gives formal guarantees, and works in the presence of an active attacker who aggressively targets parts of a system and induces faults precisely.
Gharibi_FaceCard for Contacts and Easy Personal - Information Exchange
Venue: arXiv cs.CY 2014
Year: 2014

In this paper, we discuss a new contact way for exchanging personal information using mobile phones. The idea of this invention depends on allocating a special code called Gharibi Code (GC) for each personal mobile and creating a personal information file called Gharibi Face Card (GFC), which has all specified personal data of the mobile phone user. When you request someone's GC code, the other party's phone will send you the GFC of that person. We think that this approach will facilitate the process of communication and exchanging the specified personal data easily, especially when acquaintance. Mobile number, phone and e-mail address, for example, will be sent in a few seconds using a simple code that does not exceed six characters long to transfer a huge amount of personal data through mobile devices rather than using traditional business or visiting cards.
Relative $α$-Entropy Minimizers Subject to Linear Statistical Constraints
Venue: arXiv cs.IT 2014
Year: 2014

We study minimization of a parametric family of relative entropies, termed relative $α$-entropies (denoted $\mathscr{I}_α(P,Q)$). These arise as redundancies under mismatched compression when cumulants of compressed lengths are considered instead of expected compressed lengths. These parametric relative entropies are a generalization of the usual relative entropy (Kullback-Leibler divergence). Just like relative entropy, these relative $α$-entropies behave like squared Euclidean distance and satisfy the Pythagorean property. Minimization of $\mathscr{I}_α(P,Q)$ over the first argument on a set of probability distributions that constitutes a linear family is studied. Such a minimization generalizes the maximum Rényi or Tsallis entropy principle. The minimizing probability distribution (termed $\mathscr{I}_α$-projection) for a linear family is shown to have a power-law.
Harnessing the power of Social Bookmarking for improving tag-based Recommendations
Venue: arXiv cs.SI 2014
Year: 2014

Social bookmarking and tagging has emerged a new era in user collaboration. Collaborative Tagging allows users to annotate content of their liking, which via the appropriate algorithms can render useful for the provision of product recommendations. It is the case today for tag-based algorithms to work complementary to rating-based recommendation mechanisms to predict the user liking to various products. In this paper we propose an alternative algorithm for computing personalized recommendations of products, that uses exclusively the tags provided by the users. Our approach is based on the idea of using the semantic similarity of the user-provided tags for clustering them into groups of similar meaning. Afterwards, some measurable characteristics of users' Annotation Competency are combined with other metrics, such as user similarity, for computing predictions. The evaluation on data used from a real-world collaborative tagging system, citeUlike, confirmed that our approach outperforms the baseline Vector Space model, as well as other state of the art algorithms, predicting the user liking more accurately.
On the Provenance of Linked Data Statistics
Venue: arXiv cs.DB 2014
Year: 2014

As the amount of linked data published on the web grows, attempts are being made to describe and measure it. However even basic statistics about a graph, such as its size, are difficult to express in a uniform and predictable way. In order to be able to sensibly interpret a statistic it is necessary to know how it was calculate. In this paper we survey the nature of the problem and outline a strategy for addressing it.