OpenRaiser/Intern-Atlas huggingface dataset:
Polish - English Speech Statistical Machine Translation Systems for the IWSLT 2013
Venue: arXiv cs.CL 2015
Year: 2015

This research explores the effects of various training settings from Polish to English Statistical Machine Translation system for spoken language. Various elements of the TED parallel text corpora for the IWSLT 2013 evaluation campaign were used as the basis for training of language models, and for development, tuning and testing of the translation system. The BLEU, NIST, METEOR and TER metrics were used to evaluate the effects of data preparations on translation results. Our experiments included systems, which use stems and morphological information on Polish words. We also conducted a deep analysis of provided Polish data as preparatory work for the automatic data correction and cleaning phase.
Deep Haar Scattering Networks
Venue: arXiv cs.LG 2015
Year: 2015

An orthogonal Haar scattering transform is a deep network, computed with a hierarchy of additions, subtractions and absolute values, over pairs of coefficients. It provides a simple mathematical model for unsupervised deep network learning. It implements non-linear contractions, which are optimized for classification, with an unsupervised pair matching algorithm, of polynomial complexity. A structured Haar scattering over graph data computes permutation invariant representations of groups of connected points in the graph. If the graph connectivity is unknown, unsupervised Haar pair learning can provide a consistent estimation of connected dyadic groups of points. Classification results are given on image data bases, defined on regular grids or graphs, with a connectivity which may be known or unknown.
On Jamming Against Wireless Networks
Venue: arXiv cs.IT 2015
Year: 2015

In this paper, we study jamming attacks against wireless networks. Specifically, we consider a network of base stations (BS) or access points (AP) and investigate the impact of a fixed number of jammers that are randomly deployed according to a Binomial point process. We shed light on the network performance in terms of a) the outage probability and b) the error probability of a victim receiver in the downlink of this wireless network. We derive analytical expressions for both these metrics and discuss in detail how the jammer network must adapt to the various wireless network parameters in order to effectively attack the victim receivers. For instance, we will show that with only 1 jammer per BS/AP a) the outage probability of the wireless network can be increased from 1% (as seen in the non-jamming case) to 80% and b) when retransmissions are used, the jammers cause the effective network activity factor (and hence the interference among the BSs) to be doubled. Furthermore, we show that the behavior of the jammer network as a function of the BS/AP density is not obvious. In particular, an interesting concave-type behavior is seen which indicates that the number of jammers required to attack the wireless network must scale with the BS density only until a certain value beyond which it decreases. In the context of error probability of the victim receiver, we study whether or not some recent results related to jamming in the point-to-point link scenario can be extended to the case of jamming against wireless networks. Numerical results are presented to validate the theoretical inferences presented.
Fast Algorithms for Exact String Matching
Venue: arXiv cs.DS 2015
Year: 2015

Given a pattern string $P$ of length $n$ and a query string $T$ of length $m$, where the characters of $P$ and $T$ are drawn from an alphabet of size $Δ$, the {\em exact string matching} problem consists of finding all occurrences of $P$ in $T$. For this problem, we present algorithms that in $O(nΔ^2)$ time pre-process $P$ to essentially identify $sparse(P)$, a rarely occurring substring of $P$, and then use it to find occurrences of $P$ in $T$ efficiently. Our algorithms require a worst case search time of $O(m)$, and expected search time of $O(m/min(|sparse(P)|, Δ))$, where $|sparse(P)|$ is at least $δ$ (i.e. the number of distinct characters in $P$), and for most pattern strings it is observed to be $Ω(n^{1/2})$.
Efficiently Finding All Maximal $α$-gapped Repeats
Venue: arXiv cs.DS 2015
Year: 2015

For $α\geq 1$, an $α$-gapped repeat in a word $w$ is a factor $uvu$ of $w$ such that $|uv|\leq α|u|$; the two factors $u$ in such a repeat are called arms, while the factor $v$ is called gap. Such a repeat is called maximal if its arms cannot be extended simultaneously with the same symbol to the right or, respectively, to the left. In this paper we show that the number of maximal $α$-gapped repeats that may occur in a word is upper bounded by $18αn$. This allows us to construct an algorithm finding all the maximal $α$-gapped repeats of a word in $O(αn)$; this is optimal, in the worst case, as there are words that have $Θ(αn)$ maximal $α$-gapped repeats. Our techniques can be extended to get comparable results in the case of $α$-gapped palindromes, i.e., factors $uvu^\mathrm{T}$ with $|uv|\leq α|u|$.
Fast Algorithms for Convolutional Neural Networks
Venue: arXiv cs.NE 2015
Year: 2015

Deep convolutional neural networks take GPU days of compute time to train on large data sets. Pedestrian detection for self driving cars requires very low latency. Image recognition for mobile phones is constrained by limited processing resources. The success of convolutional neural networks in these situations is limited by how fast we can compute them. Conventional FFT based convolution is fast for large filters, but state of the art convolutional neural networks use small, 3x3 filters. We introduce a new class of fast algorithms for convolutional neural networks using Winograd's minimal filtering algorithms. The algorithms compute minimal complexity convolution over small tiles, which makes them fast with small filters and small batch sizes. We benchmark a GPU implementation of our algorithm with the VGG network and show state of the art throughput at batch sizes from 1 to 64.
On Chudnovsky-Based Arithmetic Algorithms in Finite Fields
Venue: arXiv cs.DM 2015
Year: 2015

Thanks to a new construction of the so-called Chudnovsky-Chudnovsky multiplication algorithm, we design efficient algorithms for both the exponentiation and the multiplication in finite fields. They are tailored to hardware implementation and they allow computations to be parallelized while maintaining a low number of bilinear multiplications. We give an example with the finite field ${\mathbb F}_{16^{13}}$.
Higher-order asymptotics for the parametric complexity
Venue: arXiv cs.IT 2015
Year: 2015

The parametric complexity is the key quantity in the minimum description length (MDL) approach to statistical model selection. Rissanen and others have shown that the parametric complexity of a statistical model approaches a simple function of the Fisher information volume of the model as the sample size $n$ goes to infinity. This paper derives higher-order asymptotic expansions for the parametric complexity, in the case of exponential families and independent and identically distributed data. These higher-order approximations are calculated for some examples and are shown to have better finite-sample behaviour than Rissanen's approximation. The higher-order terms are given as expressions involving cumulants (or, more naturally, the Amari-Chentsov tensors), and these terms are likely to be interesting in themselves since they arise naturally from the general information-theoretic principles underpinning MDL. The derivation given here specializes to an alternative and arguably simpler proof of Rissanen's result (for the case considered here), proving for the first time that his approximation is $O(n^{-1})$.
Data Association for an Adaptive Multi-target Particle Filter Tracking System
Venue: arXiv cs.CV 2015
Year: 2015

This paper presents a novel approach to improve the accuracy of tracking multiple objects in a static scene using a particle filter system by introducing a data association step, a state queue for the collection of tracked objects and adaptive parameters to the system. The data association step makes use of the object detection phase and appearance model to determine if the approximated targets given by the particle filter step match the given set of detected objects. The remaining detected objects are used as information to instantiate new objects for tracking. State queues are also used for each tracked object to deal with occlusion events and occlusion recovery. Finally we present how the parameters adjust to occlusion events. The adaptive property of the system is also used for possible occlusion recovery. Results of the system are then compared to a ground truth data set for performance evaluation. Our system produced accurate results and was able to handle partially occluded objects as well as proper occlusion recovery from tracking multiple objects
A comparison of the performance and scalability of relational and document-based web-systems for large scale applications in a rehabilitation context
Venue: arXiv cs.CY 2015
Year: 2015

Background: The Virtual Rehabilitation Environment (VRE) provides patients of long term neurological conditions with a platform to review their previous physiotherapy sessions, as well as see their goals and any treatments or exercises that their clinician has set for them to practice before their next session. Objective: The initial application implemented 21 of the 27 core features using the Microsoft ASP.NET MVC stack. However, the two core, non-functional requirements were negated from the project due to lack of experience and strict time constraints. This project aimed to investigate whether the application would be more suited to a non-relational solution. Method: The application was re-written using the MEAN stack (MongoDB, ExpressJS, AngularJS, NodeJS), an open source, fully JavaScript stack and then performance tests were carried out to compare the two applications. A scalability review was also conducted to assess the benefits and drawbacks of each technology in this aspect. Results: The investigation proved that the non-relational solution was much more efficient and performed faster. However, the choice of database was only a small part of the increase in efficiency and it was an all-round better design that gave the new application its performance upper hand. Conclusion: A proposal for a new application design is given that follows the microservice architecture used by companies such as Amazon and Netflix. The application is to be split up into four parts; database, client application, server application and content delivery network. These four, independently scalable and manageable services offer the greatest flexibility for future development at the low costs necessary for a start-up.
Event-Cloud Platform to Support Decision- Making in Emergency Management
Venue: arXiv cs.CY 2015
Year: 2015

The challenge of this paper is to underline the capability of an Event-Cloud Platform to support efficiently an emergency situation. We chose to focus on a nuclear crisis use case. The proposed approach consists in modeling the business processes of crisis response on the one hand, and in supporting the orchestration and execution of these processes by using an Event-Cloud Platform on the other hand. This paper shows how the use of Event-Cloud techniques can support crisis management stakeholders by automatizing non-value added tasks and by directing decision- makers on what really requires their capabilities of choice. If Event-Cloud technology is a very interesting and topical subject, very few research works have considered this to improve emergency management. This paper tries to fill this gap by considering and applying these technologies on a nuclear crisis use-case.
Enduring Access to Rich Media Content: Understanding Use and Usability Requirements
Venue: arXiv cs.DL 2015
Year: 2015

Through an NEH-funded initiative, Cornell University Library is creating a technical, curatorial, and managerial framework for preserving access to complex born-digital new media objects. The Library's Rose Goldsen Archive of New Media Art provides the testbed for this project. This collection of complex interactive born-digital artworks are used by students, faculty, and artists from various disciplines. Interactive digital assets are far more complex to preserve and manage than single uniform digital media files. The preservation model developed will apply not merely to new media artworks, but to other rich digital media environments. This article describes the project's findings and discoveries, focusing on a user survey conducted with the aim of creating user profiles and use cases for born-digital assets like those in the testbed collection. The project's ultimate goal is to create a preservation and access practice grounded in thorough and practical understanding of the characteristics of digital objects and their access requirements, seen from the perspectives of collection curators and users alike. We discuss how the survey findings informed the development of an artist questionnaire to support creation of user-centric and cost-efficient preservation strategies. Although this project focuses on new media art, our methodologies and findings will inform other kinds of complex born-digital collections.
A tight bound on the size of certain separating hash families
Venue: arXiv cs.IT 2015
Year: 2015

In this paper, we present a new lower bound on the size of separating hash families of type {w_1^{q-1},w_2} where w_1 < w_2. Our result extends the paper by Guo et al. on binary frameproof codes. This bound compares well against known general bounds, and is especially useful when trying to bound the size of strong separating hash families. We also show that our new bound is tight by constructing hash families that meet the new bound with equality.
Welfare and Rationality Guarantees for the Simultaneous Multiple-Round Ascending Auction
Venue: arXiv cs.GT 2015
Year: 2015

The simultaneous multiple-round auction (SMRA) and the combinatorial clock auction (CCA) are the two primary mechanisms used to sell bandwidth. Under truthful bidding, the SMRA is known to output a Walrasian equilibrium that maximizes social welfare provided the bidder valuation functions satisfy the gross substitutes property. Recently, it was shown that the combinatorial clock auction (CCA) provides good welfare guarantees for general classes of valuation functions. This motivates the question of whether similar welfare guarantees hold for the SMRA in the case of general valuation functions. We show the answer is no. But we prove that good welfare guarantees still arise if the degree of complementarities in the bidder valuations are bounded. In particular, if bidder valuations functions are $α$-near-submodular then, under truthful bidding, the SMRA has a welfare ratio (the worst case ratio between the social welfare of the optimal allocation and the auction allocation) of at most $(1+α)$. The special case of submodular valuations, namely $α=1$, and produces individually rational solutions. However, for $α>1$, this is a bicriteria guarantee, to obtain good welfare under truthful bidding requires relaxing individual rationality. Finally, we examine what strategies are required to ensure individual rationality in the SMRA with general valuation functions. First, we provide a weak characterization, namely \emph{secure bidding}, for individual rationality. We then show that if the bidders use a profit-maximizing secure bidding strategy the welfare ratio is at most $1+α$. Consequently, by bidding securely, it is possible to obtain the same welfare guarantees as truthful bidding without the loss of individual rationality.
Local Higher-Order Statistics (LHS) describing images with statistics of local non-binarized pixel patterns
Venue: arXiv cs.CV 2015
Year: 2015

We propose a new image representation for texture categorization and facial analysis, relying on the use of higher-order local differential statistics as features. It has been recently shown that small local pixel pattern distributions can be highly discriminative while being extremely efficient to compute, which is in contrast to the models based on the global structure of images. Motivated by such works, we propose to use higher-order statistics of local non-binarized pixel patterns for the image description. The proposed model does not require either (i) user specified quantization of the space (of pixel patterns) or (ii) any heuristics for discarding low occupancy volumes of the space. We propose to use a data driven soft quantization of the space, with parametric mixture models, combined with higher-order statistics, based on Fisher scores. We demonstrate that this leads to a more expressive representation which, when combined with discriminatively learned classifiers and metrics, achieves state-of-the-art performance on challenging texture and facial analysis datasets, in low complexity setup. Further, it is complementary to higher complexity features and when combined with them improves performance.
Discrete Fresnel Transform and Its Circular Convolution
Venue: arXiv cs.IT 2015
Year: 2015

Discrete trigonometric transformations, such as the discrete Fourier and cosine/sine transforms, are important in a variety of applications due to their useful properties. For example, one well-known property is the convolution theorem for Fourier transform. In this letter, we derive a discrete Fresnel transform (DFnT) from the infinitely periodic optical gratings, as a linear trigonometric transform. Compared to the previous formulations of DFnT, the DFnT in this letter has no degeneracy, which hinders its mathematic applications, due to destructive interferences. The circular convolution property of the DFnT is studied for the first time. It is proved that the DFnT of a circular convolution of two sequences equals either one circularly convolving with the DFnT of the other. As circular convolution is a fundamental process in discrete systems, the DFnT not only gives the coefficients of the Talbot image, but can also be useful for optical and digital signal processing and numerical evaluation of the Fresnel transform.
Energy-Efficient Load-Adaptive Massive MIMO
Venue: arXiv cs.NI 2015
Year: 2015

Massive MIMO is a promising technique to meet the exponential growth of global mobile data traffic demand. However, contrary to the current systems, energy consumption of next generation networks is required to be load adaptive as the network load varies significantly throughout the day. In this paper, we propose a load adaptive massive MIMO system that varies the number of antennas following the daily load profile (DLP) in order to maximize the downlink energy efficiency (EE). A multi-cell system is considered where each base station (BS) is equipped with a large number of antennas to serve many single antenna users. In order to incorporate DLP, each BS is modeled as an M/G/m/m state dependent queue under the assumption that the network is dimensioned to serve a maximum number of users at the peak load. For a given number of users in a cell, the optimum number of active antennas maximizing EE is derived. The EE maximization problem is formulated in a game theoretic framework where the number of antennas to be used by a BS is determined through best response iteration. This load adaptive system achieves overall 19% higher EE compared to a baseline system where the BSs always run with the fixed number of antennas that is most energy efficient at peak load and that can be switched-off when there is no traffic
It is not all downhill from here: Syllable Contact Law in Persian
Venue: arXiv cs.CL 2015
Year: 2015

Syllable contact pairs crosslinguistically tend to have a falling sonority slope a constraint which is called the Syllable Contact Law SCL In this study the phonotactics of syllable contacts in 4202 CVCCVC words of Persian lexicon is investigated The consonants of Persian were divided into five sonority categories and the frequency of all possible sonority slopes is computed both in lexicon type frequency and in corpus token frequency Since an unmarked phonological structure has been shown to diachronically become more frequent we expect to see the same pattern for syllable contact pairs with falling sonority slope The correlation of sonority categories of the two consonants in a syllable contact pair is measured using Pointwise Mutual Information
A Note on Finding Dual Feedback Vertex Set
Venue: arXiv cs.DS 2015
Year: 2015

For an edge-bicolored graph $G$ where each edge is colored either red or blue, a vertex set $S$ is a dual feedback vertex set if $S$ hits all blue cycles and red cycles of $G$. In this paper, we show that a dual feedback vertex set of size at most $k$ can be found in time $O^*(c_1^k)$ and all minimal dual feedback vertex set of size at most $k$ can be enumerated in time $O^*(c_2^{k^2 + k})$ by compact representations for constants $c_1$ and $c_2$.
A Fast Survey on Methods for Classification Anonymity Requirements
Venue: arXiv cs.CR 2015
Year: 2015

Anonymity has become a significant issue in security field by recent advances in information technology and internet. The main objective of anonymity is hiding and concealing entities privacy inside a system. Many methods and protocols have been proposed with different anonymity services to provide anonymity requirements in various fields until now. Each anonymity method or protocol is developed using particular approach. In this paper, first, accurate and perfect definitions of privacy and anonymity are presented then most important problems in anonymity field are investigated. Afterwards, the numbers of main anonymity protocols are described with necessary details. Finally, all findings are concluded and some more future perspectives are discussed.
Intelligent Search Optimization using Artificial Fuzzy Logics
Venue: arXiv cs.AI 2015
Year: 2015

Information on the web is prodigious; searching relevant information is difficult making web users to rely on search engines for finding relevant information on the web. Search engines index and categorize web pages according to their contents using crawlers and rank them accordingly. For given user query they retrieve millions of webpages and display them to users according to web-page rank. Every search engine has their own algorithms based on certain parameters for ranking web-pages. Search Engine Optimization (SEO) is that technique by which webmasters try to improve ranking of their websites by optimizing it according to search engines ranking parameters. It is the aim of this research to identify the most popular SEO techniques used by search engines for ranking web-pages and to establish their importance for indexing and categorizing web data. The research tries to establish that using more SEO parameters in ranking algorithms helps in retrieving better search results thus increasing user satisfaction. In the accomplished research, a web based Meta search engine is proposed to aggregates search results from different search engines and rank web-pages based on new page ranking algorithm which will assign heuristic page rank to web-pages based on SEO parameters such as title tag, Meta description, sitemap etc. The research also provides insight into techniques which webmasters can use for better ranking their websites in Google and Bing. Initial results has shown that using certain SEO parameters in present ranking algorithm helps in retrieving more useful results for user queries. These results generated from Meta search engine outperformed existing search engines in terms of better retrieved search results and high precision.