OpenRaiser/Intern-Atlas huggingface dataset:
Analyzing of MOS and Codec Selection for Voice over IP Technology
Venue: arXiv cs.NI 2009
Year: 2009

In this research, we propose an architectural solution to implement the voice over IP (VoIP) service in campus environment network. Voice over IP (VoIP) technology has become a discussion issue for this time being. Today, the deployment of this technology on an organization truly can give a great financial benefit over traditional telephony. Therefore, this study is to analyze the VoIP Codec selection and investigate the Mean Opinion Score (MOS) performance areas evolved with the quality of service delivered by soft phone and IP phone. This study focuses on quality of voice prediction such as i) accuracy of MOS between automated system and human perception and ii) different types of codec performance measurement via human perception using MOS technique. In this study, network management system (NMS) is used to monitor and capture the performance of VoIP in campus environment. In addition, the most apparent of implementing soft phone and IP phone in campus environment is to define the best codec selection that can be used in operational environment. Based on the finding result, the MOS measurement through automated and manual system is able to predict and evaluate VoIP performance. In addition, based on manual MOS measurement, VoIP conversations over LAN contribute more reliability and availability performance compare to WAN.
Using Genetic Algorithms for Texts Classification Problems
Venue: arXiv cs.LG 2009
Year: 2009

The avalanche quantity of the information developed by mankind has led to concept of automation of knowledge extraction - Data Mining ([1]). This direction is connected with a wide spectrum of problems - from recognition of the fuzzy set to creation of search machines. Important component of Data Mining is processing of the text information. Such problems lean on concept of classification and clustering ([2]). Classification consists in definition of an accessory of some element (text) to one of in advance created classes. Clustering means splitting a set of elements (texts) on clusters which quantity are defined by localization of elements of the given set in vicinities of these some natural centers of these clusters. Realization of a problem of classification initially should lean on the given postulates, basic of which - the aprioristic information on primary set of texts and a measure of affinity of elements and classes.
Upon the Modeling and the Optimization of the Debiting Process through Computer Aided Non-Conventional Technologies
Venue: arXiv cs.OH 2009
Year: 2009

The debiting process of the remarkable properties materials can be managed through unconventional technologies as the complex electrical erosion. We present the modeling of the previous experimental results to obtain a mathematical dependence of the output parameters (processing time, surface quality) on the input parameters (voltage or current). All the experimental data are memorized on a database and for each particular debiting process a new dependence is built. Because all the experiments applied in the Romanian laboratories or practical applications of the nonconventional technological processes in the factories were based on the particular conditions of one activity, this papers presents the technical implementation of a computer-aided solution that keeps all previous experimental data, optimizes the processing conditions and eventual manage the driving gear. The flow-chart we present in this paper offers a solution for practitioners to reduce the electrical consumption while a technological processing of special materials is necessary. The computer program and the database can be easily adapted to any technological processes (conventional or not).
Report on the current state of the French DMLs
Venue: arXiv cs.DL 2009
Year: 2009

This is a survey of the existing digital collections of French mathematical literature, run by non-profit organizations. This includes research monographs, serials, proceedings, Ph. D. theses, collected works, books and personal websites.
A Full Image of the Wormhole Attacks - Towards Introducing Complex Wormhole Attacks in wireless Ad Hoc Networks
Venue: arXiv cs.CR 2009
Year: 2009

The paper analyzes wormhole attack modes and classes and point to its threat impacts on ad hoc networks. New improvements are suggested to these types of attacks.
Efficient Algorithms for Several Constrained Activity Scheduling Problems in the Time and Space Domains
Venue: arXiv cs.DS 2009
Year: 2009

In this paper we consider several constrained activity scheduling problems in the time and space domains, like finding activity orderings which optimize the values of several objective functions (time scheduling) or finding optimal locations where certain types of activities will take place (space scheduling). We present novel, efficient algorithmic solutions for all the considered problems, based on the dynamic programming and greedy techniques. In each case we compute exact, optimal solutions.
A Step-indexed Semantics of Imperative Objects
Venue: arXiv cs.PL 2009
Year: 2009

Step-indexed semantic interpretations of types were proposed as an alternative to purely syntactic proofs of type safety using subject reduction. The types are interpreted as sets of values indexed by the number of computation steps for which these values are guaranteed to behave like proper elements of the type. Building on work by Ahmed, Appel and others, we introduce a step-indexed semantics for the imperative object calculus of Abadi and Cardelli. Providing a semantic account of this calculus using more `traditional', domain-theoretic approaches has proved challenging due to the combination of dynamically allocated objects, higher-order store, and an expressive type system. Here we show that, using step-indexing, one can interpret a rich type discipline with object types, subtyping, recursive and bounded quantified types in the presence of state.
Cell-Probe Lower Bounds for Prefix Sums
Venue: arXiv cs.CC 2009
Year: 2009

We prove that to store n bits x so that each prefix-sum query Sum(i) := sum_{k < i} x_k can be answered by non-adaptively probing q cells of log n bits, one needs memory > n + n/log^{O(q)} n. Our bound matches a recent upper bound of n + n/log^{Omega(q)} n by Patrascu (FOCS 2008), also non-adaptive. We also obtain a n + n/log^{2^{O(q)}} n lower bound for storing a string of balanced brackets so that each Match(i) query can be answered by non-adaptively probing q cells. To obtain these bounds we show that a too efficient data structure allows us to break the correlations between query answers.
Analyser Framework to verify Software Component
Venue: arXiv cs.SE 2009
Year: 2009

Today, it is important for software companies to build software systems in a short time-interval, to reduce costs and to have a good market position. Therefore well organized and systematic development approaches are required. Reusing software components, which are well tested, can be a good solution to develop software applications in effective manner. The reuse of software components is less expensive and less time consuming than a development from scratch. But it is dangerous to think that software components can be match together without any problems. Software components itself are well tested, of course, but even if they composed together problems occur. Most problems are based on interaction respectively communication. Avoiding such errors a framework has to be developed for analysing software components. That framework determines the compatibility of corresponding software components.The promising approach discussed here, presents a novel technique for analysing software components by applying an Abstract Syntax Language Tree (ASLT). A supportive environment will be designed that checks the compatibility of black-box software components. This article is concerned to the question how can be coupled software components verified by using an analyzer framework and determines the usage of the ASLT. Black-box Software Components and Abstract Syntax Language Tree are the basis for developing the proposed framework and are discussed here to provide the background knowledge. The practical implementation of this framework is discussed and shows the result by using a test environment.
Approximating the Permanent via Nonabelian Determinants
Venue: arXiv cs.CC 2009
Year: 2009

Celebrated work of Jerrum, Sinclair, and Vigoda has established that the permanent of a {0,1} matrix can be approximated in randomized polynomial time by using a rapidly mixing Markov chain. A separate strand of the literature has pursued the possibility of an alternate, purely algebraic, polynomial-time approximation scheme. These schemes work by replacing each 1 with a random element of an algebra A, and considering the determinant of the resulting matrix. When A is noncommutative, this determinant can be defined in several ways. We show that for estimators based on the conventional determinant, the critical ratio of the second moment to the square of the first--and therefore the number of trials we need to obtain a good estimate of the permanent--is (1 + O(1/d))^n when A is the algebra of d by d matrices. These results can be extended to group algebras, and semi-simple algebras in general. We also study the symmetrized determinant of Barvinok, showing that the resulting estimator has small variance when d is large enough. However, for constant d--the only case in which an efficient algorithm is known--we show that the critical ratio exceeds 2^{n} / n^{O(d)}. Thus our results do not provide a new polynomial-time approximation scheme for the permanent. Indeed, they suggest that the algebraic approach to approximating the permanent faces significant obstacles. We obtain these results using diagrammatic techniques in which we express matrix products as contractions of tensor products. When these matrices are random, in either the Haar measure or the Gaussian measure, we can evaluate the trace of these products in terms of the cycle structure of a suitably random permutation. In the symmetrized case, our estimates are then derived by a connection with the character theory of the symmetric group.
Large-Margin kNN Classification Using a Deep Encoder Network
Venue: arXiv cs.LG 2009
Year: 2009

KNN is one of the most popular classification methods, but it often fails to work well with inappropriate choice of distance metric or due to the presence of numerous class-irrelevant features. Linear feature transformation methods have been widely applied to extract class-relevant information to improve kNN classification, which is very limited in many applications. Kernels have been used to learn powerful non-linear feature transformations, but these methods fail to scale to large datasets. In this paper, we present a scalable non-linear feature mapping method based on a deep neural network pretrained with restricted boltzmann machines for improving kNN classification in a large-margin framework, which we call DNet-kNN. DNet-kNN can be used for both classification and for supervised dimensionality reduction. The experimental results on two benchmark handwritten digit datasets show that DNet-kNN has much better performance than large-margin kNN using a linear mapping and kNN based on a deep autoencoder pretrained with retricted boltzmann machines.
A Randomized Algorithm for 3-SAT
Venue: arXiv cs.DS 2009
Year: 2009

In this work we propose and analyze a simple randomized algorithm to find a satisfiable assignment for a Boolean formula in conjunctive normal form (CNF) having at most 3 literals in every clause. Given a k-CNF formula phi on n variables, and alpha in{0,1}^n that satisfies phi, a clause of phi is critical if exactly one literal of that clause is satisfied under assignment alpha. Paturi et. al. (Chicago Journal of Theoretical Computer Science 1999) proposed a simple randomized algorithm (PPZ) for k-SAT for which success probability increases with the number of critical clauses (with respect to a fixed satisfiable solution of the input formula). Here, we first describe another simple randomized algorithm DEL which performs better if the number of critical clauses are less (with respect to a fixed satisfiable solution of the input formula). Subsequently, we combine these two simple algorithms such that the success probability of the combined algorithm is maximum of the success probabilities of PPZ and DEL on every input instance. We show that when the average number of clauses per variable that appear as unique true literal in one or more critical clauses in phi is between 1 and 1.9317, combined algorithm performs better than the PPZ algorithm.
Dependable Distributed Computing for the International Telecommunication Union Regional Radio Conference RRC06
Venue: arXiv cs.DC 2009
Year: 2009

The International Telecommunication Union (ITU) Regional Radio Conference (RRC06) established in 2006 a new frequency plan for the introduction of digital broadcasting in European, African, Arab, CIS countries and Iran. The preparation of the plan involved complex calculations under short deadline and required dependable and efficient computing capability. The ITU designed and deployed in-situ a dedicated PC farm, in parallel to the European Organization for Nuclear Research (CERN) which provided and supported a system based on the EGEE Grid. The planning cycle at the RRC06 required a periodic execution in the order of 200,000 short jobs, using several hundreds of CPU hours, in a period of less than 12 hours. The nature of the problem required dynamic workload-balancing and low-latency access to the computing resources. We present the strategy and key technical choices that delivered a reliable service to the RRC06.
Revisiting Digital Straight Segment Recognition
Venue: arXiv cs.DM 2009
Year: 2009

This paper presents new results about digital straight segments, their recognition and related properties. They come from the study of the arithmetically based recognition algorithm proposed by I. Debled-Rennesson and J.-P. Reveillès in 1995 [Debled95]. We indeed exhibit the relations describing the possible changes in the parameters of the digital straight segment under investigation. This description is achieved by considering new parameters on digital segments: instead of their arithmetic description, we examine the parameters related to their combinatoric description. As a result we have a better understanding of their evolution during recognition and analytical formulas to compute them. We also show how this evolution can be projected onto the Stern-Brocot tree. These new relations have interesting consequences on the geometry of digital curves. We show how they can for instance be used to bound the slope difference between consecutive maximal segments.
Ftklipse - Design and Implementation of an Extendable Computer Forensics Environment: Software Requirements Specification Document
Venue: arXiv cs.CR 2009
Year: 2009

The purpose behind this article is to describe the features of Ftklipse, an extendable platform for computer forensics. This document designed to provide a detailed specification for the developers of Ftklipse. Ftklipse is a thick-client solution for forensics investigation. It is designed to collect and preserve evidence, to analyze it and to report on it. It supports chain of custody management, access control policies, and batch operation of its included tools in order to facilitate and accelerate the investigation. The environment itself and its tools are configurable as well and is based on Eclipse.
The Limit of Convexity Based Isoperimetry: Sampling Harmonic-Concave Functions
Venue: arXiv cs.DS 2009
Year: 2009

Logconcave functions represent the current frontier of efficient algorithms for sampling, optimization and integration in R^n. Efficient sampling algorithms to sample according to a probability density (to which the other two problems can be reduced) relies on good isoperimetry which is known to hold for arbitrary logconcave densities. In this paper, we extend this frontier in two ways: first, we characterize convexity-like conditions that imply good isoperimetry, i.e., what condition on function values along every line guarantees good isoperimetry? The answer turns out to be the set of (1/(n-1))-harmonic concave functions in R^n; we also prove that this is the best possible characterization along every line, of functions having good isoperimetry. Next, we give the first efficient algorithm for sampling according to such functions with complexity depending on a smoothness parameter. Further, noting that the multivariate Cauchy density is an important distribution in this class, we exploit certain properties of the Cauchy density to give an efficient sampling algorithm based on random walks with a mixing time that matches the current best bounds known for sampling logconcave functions.
Continuous Blooming of Convex Polyhedra
Venue: arXiv cs.CG 2009
Year: 2009

We construct the first two continuous bloomings of all convex polyhedra. First, the source unfolding can be continuously bloomed. Second, any unfolding of a convex polyhedron can be refined (further cut, by a linear number of cuts) to have a continuous blooming.
Truthful Mechanisms via Greedy Iterative Packing
Venue: arXiv cs.GT 2009
Year: 2009

An important research thread in algorithmic game theory studies the design of efficient truthful mechanisms that approximate the optimal social welfare. A fundamental question is whether an α-approximation algorithm translates into an α-approximate truthful mechanism. It is well-known that plugging an α-approximation algorithm into the VCG technique may not yield a truthful mechanism. Thus, it is natural to investigate properties of approximation algorithms that enable their use in truthful mechanisms. The main contribution of this paper is to identify a useful and natural property of approximation algorithms, which we call loser-independence; this property is applicable in the single-minded and single-parameter settings. Intuitively, a loser-independent algorithm does not change its outcome when the bid of a losing agent increases, unless that agent becomes a winner. We demonstrate that loser-independent algorithms can be employed as sub-procedures in a greedy iterative packing approach while preserving monotonicity. A greedy iterative approach provides a good approximation in the context of maximizing a non-decreasing submodular function subject to independence constraints. Our framework gives rise to truthful approximation mechanisms for various problems. Notably, some problems arise in online mechanism design.
Data Structures for Approximate Range Counting
Venue: arXiv cs.DS 2009
Year: 2009

We present new data structures for approximately counting the number of points in orthogonal range. There is a deterministic linear space data structure that supports updates in O(1) time and approximates the number of elements in a 1-D range up to an additive term $k^{1/c}$ in $O(\log \log U\cdot\log \log n)$ time, where $k$ is the number of elements in the answer, $U$ is the size of the universe and $c$ is an arbitrary fixed constant. We can estimate the number of points in a two-dimensional orthogonal range up to an additive term $ k^ρ$ in $O(\log \log U+ (1/ρ)\log\log n)$ time for any $ρ>0$. We can estimate the number of points in a three-dimensional orthogonal range up to an additive term $k^ρ$ in $O(\log \log U + (\log\log n)^3+ (3^v)\log\log n)$ time for $v=\log \frac{1}ρ/\log {3/2}+2$.
Partial randomness and dimension of recursively enumerable reals
Venue: arXiv cs.CC 2009
Year: 2009

A real αis called recursively enumerable ("r.e." for short) if there exists a computable, increasing sequence of rationals which converges to α. It is known that the randomness of an r.e. real αcan be characterized in various ways using each of the notions; program-size complexity, Martin-Löf test, Chaitin Ωnumber, the domination and Ω-likeness of α, the universality of a computable, increasing sequence of rationals which converges to α, and universal probability. In this paper, we generalize these characterizations of randomness over the notion of partial randomness by parameterizing each of the notions above by a real T in (0,1], where the notion of partial randomness is a stronger representation of the compression rate by means of program-size complexity. As a result, we present ten equivalent characterizations of the partial randomness of an r.e. real. The resultant characterizations of partial randomness are powerful and have many important applications. One of them is to present equivalent characterizations of the dimension of an individual r.e. real. The equivalence between the notion of Hausdorff dimension and compression rate by program-size complexity (or partial randomness) has been established at present by a series of works of many researchers over the last two decades. We present ten equivalent characterizations of the dimension of an individual r.e. real.
Employing Wikipedia's Natural Intelligence For Cross Language Information Retrieval
Venue: arXiv cs.IR 2009
Year: 2009

In this paper we present a novel method for retrieving information in languages other than that of the query. We use this technique in combination with existing traditional Cross Language Information Retrieval (CLIR) techniques to improve their results. This method has a number of advantages over traditional techniques that rely on machine translation to translate the query and then search the target document space using a machine translation. This method is not limited to the availability of a machine translation algorithm for the desired language and uses already existing sources of readily available translated information on the internet as a "middle-man" approach. In this paper we use Wikipedia; however, any similar multilingual, cross referenced body of documents can be used. For evaluation and comparison purposes we also implemented a traditional machine translation approach separately as well as the Wikipedia approach separately.
Efficient Multi-site Data Movement Using Constraint Programming for Data Hungry Science
Venue: arXiv cs.DC 2009
Year: 2009

For the past decade, HENP experiments have been heading towards a distributed computing model in an effort to concurrently process tasks over enormous data sets that have been increasing in size as a function of time. In order to optimize all available resources (geographically spread) and minimize the processing time, it is necessary to face also the question of efficient data transfers and placements. A key question is whether the time penalty for moving the data to the computational resources is worth the presumed gain. Onward to the truly distributed task scheduling we present the technique using a Constraint Programming (CP) approach. The CP technique schedules data transfers from multiple resources considering all available paths of diverse characteristic (capacity, sharing and storage) having minimum user's waiting time as an objective. We introduce a model for planning data transfers to a single destination (data transfer) as well as its extension for an optimal data set spreading strategy (data placement). Several enhancements for a solver of the CP model will be shown, leading to a faster schedule computation time using symmetry breaking, branch cutting, well studied principles from job-shop scheduling field and several heuristics. Finally, we will present the design and implementation of a corner-stone application aimed at moving datasets according to the schedule. Results will include comparison of performance and trade-off between CP techniques and a Peer-2-Peer model from simulation framework as well as the real case scenario taken from a practical usage of a CP scheduler.