OpenRaiser/Intern-Atlas huggingface dataset:
Data Life Cycle Labs, A New Concept to Support Data-Intensive Science
Venue: arXiv cs.DL 2012
Year: 2012

In many sciences the increasing amounts of data are reaching the limit of established data handling and processing. With four large research centers of the German Helmholtz association the Large Scale Data Management and Analysis (LSDMA) project supports an initial set of scientific projects, initiatives and instruments to organize and efficiently analyze the increasing amount of data produced in modern science. LSDMA bridges the gap between data production and data analysis using a novel approach by combining specific community support and generic, cross community development. In the Data Life Cycle Labs (DLCL) experts from the data domain work closely with scientific groups of selected research domains in joint R&D where community-specific data life cycles are iteratively optimized, data and meta-data formats are defined and standardized, simple access and use is established as well as data and scientific insights are preserved in long-term and open accessible archives.
Elaboration of a new tool for weather data sequences generation
Venue: arXiv cs.CE 2012
Year: 2012

This paper deals about the presentation of a new software RUNEOLE used to provide weather data in buildings physics. RUNEOLE associates three modules leading to the description, the modelling and the generation of weather data. The first module is dedicated to the description of each climatic variable included in the database. Graphic representation is possible (with histograms for example). Mathematical tools used to compare statistical distributions, determine daily characteristic evolutions, find typical days, and the correlations between the different climatic variables have been elaborated in the second module. Artificial weather datafiles adapted to different simulation codes are available at the issue of the third module. This tool can then be used in HVAC system evaluation, or in the study of thermal comfort. The studied buildings can then be tested under different thermal, aeraulic, and radiative solicitations, leading to a best understanding of their behaviour for example in humid climates.
Design, implementation and experiment of a YeSQL Web Crawler
Venue: arXiv cs.IR 2012
Year: 2012

We describe a novel, "focusable", scalable, distributed web crawler based on GNU/Linux and PostgreSQL that we designed to be easily extendible and which we have released under a GNU public licence. We also report a first use case related to an analysis of Twitter's streams about the french 2012 presidential elections and the URL's it contains.
Partout: A Distributed Engine for Efficient RDF Processing
Venue: arXiv cs.DB 2012
Year: 2012

The increasing interest in Semantic Web technologies has led not only to a rapid growth of semantic data on the Web but also to an increasing number of backend applications with already more than a trillion triples in some cases. Confronted with such huge amounts of data and the future growth, existing state-of-the-art systems for storing RDF and processing SPARQL queries are no longer sufficient. In this paper, we introduce Partout, a distributed engine for efficient RDF processing in a cluster of machines. We propose an effective approach for fragmenting RDF data sets based on a query log, allocating the fragments to nodes in a cluster, and finding the optimal configuration. Partout can efficiently handle updates and its query optimizer produces efficient query execution plans for ad-hoc SPARQL queries. Our experiments show the superiority of our approach to state-of-the-art approaches for partitioning and distributed SPARQL query processing.
Algorithm to Compute Squares of 1st N Natural Numbers Without Using Multiplication
Venue: arXiv cs.DS 2012
Year: 2012

Processors may find some elementary operations to be faster than the others. Although an operation may be conceptually as simple as some other operation, the processing speeds of the two can vary. A clever programmer will always try to choose the faster instructions for the job. This paper presents an algorithm to display squares of 1st N natural numbers without using multiplication (* operator). Instead, the same work can be done using addition (+ operator). The results can also be used to compute the sum of those squares. If we compare the normal method of computing the squares of 1st N natural numbers with this method, we can conclude that the algorithm discussed in the paper is more optimized in terms of time complexity.
On the decoding of quasi-BCH codes
Venue: arXiv cs.IT 2012
Year: 2012

In this paper we investigate the structure of quasi-BCH codes. In the first part of this paper we show that quasi-BCH codes can be derived from Reed-Solomon codes over square matrices extending the known relation about classical BCH and Reed-Solomon codes. This allows us to adapt the Welch-Berlekamp algorithm to quasi-BCH codes. In the second part of this paper we show that quasi-BCH codes can be seen as subcodes of interleaved Reed-Solomon codes over finite fields. This provides another approach for decoding quasi-BCH codes.
Abstract Effects and Proof-Relevant Logical Relations
Venue: arXiv cs.PL 2012
Year: 2012

We introduce a novel variant of logical relations that maps types not merely to partial equivalence relations on values, as is commonly done, but rather to a proof-relevant generalisation thereof, namely setoids. The objects of a setoid establish that values inhabit semantic types, whilst its morphisms are understood as proofs of semantic equivalence. The transition to proof-relevance solves two well-known problems caused by the use of existential quantification over future worlds in traditional Kripke logical relations: failure of admissibility, and spurious functional dependencies. We illustrate the novel format with two applications: a direct-style validation of Pitts and Stark's equivalences for "new" and a denotational semantics for a region-based effect system that supports type abstraction in the sense that only externally visible effects need to be tracked; non-observable internal modifications, such as the reorganisation of a search tree or lazy initialisation, can count as `pure' or `read only'. This `fictional purity' allows clients of a module soundly to validate more effect-based program equivalences than would be possible with traditional effect systems.
ADADELTA: An Adaptive Learning Rate Method
Venue: arXiv cs.LG 2012
Year: 2012

We present a novel per-dimension learning rate method for gradient descent called ADADELTA. The method dynamically adapts over time using only first order information and has minimal computational overhead beyond vanilla stochastic gradient descent. The method requires no manual tuning of a learning rate and appears robust to noisy gradient information, different model architecture choices, various data modalities and selection of hyperparameters. We show promising results compared to other methods on the MNIST digit classification task using a single machine and on a large scale voice dataset in a distributed cluster environment.
Random Access with Physical-layer Network Coding
Venue: arXiv cs.IT 2012
Year: 2012

Leveraging recent progress in physical-layer network coding we propose a new approach to random access: When packets collide, it is possible to recover a linear combination of the packets at the receiver. Over many rounds of transmission, the receiver can thus obtain many linear combinations and eventually recover all original packets. This is by contrast to slotted ALOHA where packet collisions lead to complete erasures. The throughput of the proposed strategy is derived and shown to be significantly superior to the best known strategies, including multipacket reception.
A Large-Scale Study of Online Shopping Behavior
Venue: arXiv cs.CY 2012
Year: 2012

The continuous growth of electronic commerce has stimulated great interest in studying online consumer behavior. Given the significant growth in online shopping, better understanding of customers allows better marketing strategies to be designed. While studies of online shopping attitude are widespread in the literature, studies of browsing habits differences in relation to online shopping are scarce. This research performs a large scale study of the relationship between Internet browsing habits of users and their online shopping behavior. Towards this end, we analyze data of 88,637 users who have bought more in total half a milion products from the retailer sites Amazon and Walmart. Our results indicate that even coarse-grained Internet browsing behavior has predictive power in terms of what users will buy online. Furthermore, we discover both surprising (e.g., "expensive products do not come with more effort in terms of purchase") and expected (e.g., "the more loyal a user is to an online shop, the less effort they spend shopping") facts. Given the lack of large-scale studies linking online browsing and online shopping behavior, we believe that this work is of general interest to people working in related areas.
An ideal multi-secret sharing scheme based on minimal privileged coalitions
Venue: arXiv cs.CR 2012
Year: 2012

How to construct an ideal multi-secret sharing scheme for general access structures is difficult. In this paper, we solve an open problem proposed by Spiez et al.recently [Finite Fields and Their Application, 2011(17) 329-342], namely to design an algorithm of privileged coalitions of any length if such coalitions exist. Furthermore, in terms of privileged coalitions, we show that most of the existing multi-secret sharing schemes based on Shamir threshold secret sharing are not perfect by analyzing Yang et al.'s scheme and Pang et al.'s scheme. Finally, based on the algorithm mentioned above, we devise an ideal multi-secret sharing scheme for families of access structures, which possesses more vivid authorized sets than that of the threshold scheme.
New design of Robotics Remote lab
Venue: arXiv cs.RO 2012
Year: 2012

The Robotic Remote Laboratory controls the Robot labs via the Internet and applies the Robot experiment in easy and advanced way. If we want to enhance the RRL system, we must study requirements of the Robot experiment in a deeply way. One of key requirements of the Robot experiment is the Control algorithm that includes all important activities to affect the Robot; one of them relates the path or obstacle. Our goal is to produce a new design of the RRL includes a new treatment to the Control algorithm depends on isolation one of the Control algorithm's activities that relates the paths in a separated algorithm, i.e., design the (Path planning algorithm) is independent of the original Control algorithm. This aim can be achieved by depending on the light to produce the Light obstacle. To apply the Light obstacle, we need to hardware (Light control server and Light arms) and soft ware (path planning algorithm).The NXT 2.0 Robot will sense the Light obstacle depending on the Light sensor of it. The new design has two servers, one for the path (Light control server) and other for the other activities of the Control algorithm (Robot control server).The website of the new design includes three main parts (Lab Reservation, Open Lab, Download Simulation).We proposed a set of scenarios for organizing the reservation of the Remote Lab. Additionally, we developed an appropriate software to simulate the Robot and to practice it before usage the Remote lab.
High Quality Image Interpolation via Local Autoregressive and Nonlocal 3-D Sparse Regularization
Venue: arXiv cs.MM 2012
Year: 2012

In this paper, we propose a novel image interpolation algorithm, which is formulated via combining both the local autoregressive (AR) model and the nonlocal adaptive 3-D sparse model as regularized constraints under the regularization framework. Estimating the high-resolution image by the local AR regularization is different from these conventional AR models, which weighted calculates the interpolation coefficients without considering the rough structural similarity between the low-resolution (LR) and high-resolution (HR) images. Then the nonlocal adaptive 3-D sparse model is formulated to regularize the interpolated HR image, which provides a way to modify these pixels with the problem of numerical stability caused by AR model. In addition, a new Split-Bregman based iterative algorithm is developed to solve the above optimization problem iteratively. Experiment results demonstrate that the proposed algorithm achieves significant performance improvements over the traditional algorithms in terms of both objective quality and visual perception
A Method to determine Partial Weight Enumerator for Linear Block Codes
Venue: arXiv cs.IT 2012
Year: 2012

In this paper we present a fast and efficient method to find partial weight enumerator (PWE) for binary linear block codes by using the error impulse technique and Monte Carlo method. This PWE can be used to compute an upper bound of the error probability for the soft decision maximum likelihood decoder (MLD). As application of this method we give partial weight enumerators and analytical performances of the BCH(130,66), BCH(103,47) and BCH(111,55) shortened codes; the first code is obtained by shortening the binary primitive BCH (255,191,17) code and the two other codes are obtained by shortening the binary primitive BCH(127,71,19) code. The weight distributions of these three codes are unknown at our knowledge.
Hyperplane Arrangements and Locality-Sensitive Hashing with Lift
Venue: arXiv cs.LG 2012
Year: 2012

Locality-sensitive hashing converts high-dimensional feature vectors, such as image and speech, into bit arrays and allows high-speed similarity calculation with the Hamming distance. There is a hashing scheme that maps feature vectors to bit arrays depending on the signs of the inner products between feature vectors and the normal vectors of hyperplanes placed in the feature space. This hashing can be seen as a discretization of the feature space by hyperplanes. If labels for data are given, one can determine the hyperplanes by using learning algorithms. However, many proposed learning methods do not consider the hyperplanes' offsets. Not doing so decreases the number of partitioned regions, and the correlation between Hamming distances and Euclidean distances becomes small. In this paper, we propose a lift map that converts learning algorithms without the offsets to the ones that take into account the offsets. With this method, the learning methods without the offsets give the discretizations of spaces as if it takes into account the offsets. For the proposed method, we input several high-dimensional feature data sets and studied the relationship between the statistical characteristics of data, the number of hyperplanes, and the effect of the proposed method.
Finding Nemo: Searching and Resolving Identities of Users Across Online Social Networks
Venue: arXiv cs.SI 2012
Year: 2012

An online user joins multiple social networks in order to enjoy different services. On each joined social network, she creates an identity and constitutes its three major dimensions namely profile, content and connection network. She largely governs her identity formulation on any social network and therefore can manipulate multiple aspects of it. With no global identifier to mark her presence uniquely in the online domain, her online identities remain unlinked, isolated and difficult to search. Earlier research has explored the above mentioned dimensions, to search and link her multiple identities with an assumption that the considered dimensions have been least disturbed across her identities. However, majority of the approaches are restricted to exploitation of one or two dimensions. We make a first attempt to deploy an integrated system (Finding Nemo) which uses all the three dimensions of an identity to search for a user on multiple social networks. The system exploits a known identity on one social network to search for her identities on other social networks. We test our system on two most popular and distinct social networks - Twitter and Facebook. We show that the integrated system gives better accuracy than the individual algorithms. We report experimental findings in the report.
Development of Low Cost Private Office Access Control System (OACS)
Venue: arXiv cs.OH 2012
Year: 2012

Over the years, access control systems have become more and more sophisticated and several security measures have been employed to combat the menace of insecurity of lives and property. This is done by preventing unauthorized entrance into buildings through entrance doors using conventional and electronic locks, discrete access code, and biometric methods such as the finger prints, thumb prints, the iris and facial recognition. We have designed a flexible and low cost modular system based on integration of keypad, magnetic lock and a controller. PIC 16F876A which is an 8-bit Microcontroller, is used here as a main controller. An advanced simulation based compiler Flowcode V4 is used to develop the software part in this project.
Echo State Queueing Network: a new reservoir computing learning tool
Venue: arXiv cs.NE 2012
Year: 2012

In the last decade, a new computational paradigm was introduced in the field of Machine Learning, under the name of Reservoir Computing (RC). RC models are neural networks which a recurrent part (the reservoir) that does not participate in the learning process, and the rest of the system where no recurrence (no neural circuit) occurs. This approach has grown rapidly due to its success in solving learning tasks and other computational applications. Some success was also observed with another recently proposed neural network designed using Queueing Theory, the Random Neural Network (RandNN). Both approaches have good properties and identified drawbacks. In this paper, we propose a new RC model called Echo State Queueing Network (ESQN), where we use ideas coming from RandNNs for the design of the reservoir. ESQNs consist in ESNs where the reservoir has a new dynamics inspired by recurrent RandNNs. The paper positions ESQNs in the global Machine Learning area, and provides examples of their use and performances. We show on largely used benchmarks that ESQNs are very accurate tools, and we illustrate how they compare with standard ESNs.
URI Identity and Web Architecture Revisited
Venue: arXiv cs.OH 2012
Year: 2012

This document reexamined the URI's identity issue and the debate regarding the nature of "information resource". By making emphasis on the abstract nature of resource and the role of URI as an interface to the web, this article presented an alternative viewpoint about the architecture of the web that would allow us to objectively and consistently treat all kinds of resources.
Heuristics Miners for Streaming Event Data
Venue: arXiv cs.DB 2012
Year: 2012

More and more business activities are performed using information systems. These systems produce such huge amounts of event data that existing systems are unable to store and process them. Moreover, few processes are in steady-state and due to changing circumstances processes evolve and systems need to adapt continuously. Since conventional process discovery algorithms have been defined for batch processing, it is difficult to apply them in such evolving environments. Existing algorithms cannot cope with streaming event data and tend to generate unreliable and obsolete results. In this paper, we discuss the peculiarities of dealing with streaming event data in the context of process mining. Subsequently, we present a general framework for defining process mining algorithms in settings where it is impossible to store all events over an extended period or where processes evolve while being analyzed. We show how the Heuristics Miner, one of the most effective process discovery algorithms for practical applications, can be modified using this framework. Different stream-aware versions of the Heuristics Miner are defined and implemented in ProM. Moreover, experimental results on artificial and real logs are reported.
Joint Sensing and Power Allocation in Nonconvex Cognitive Radio Games: Nash Equilibria and Distributed Algorithms
Venue: arXiv cs.IT 2012
Year: 2012

In this paper, we propose a novel class of Nash problems for Cognitive Radio (CR) networks, modeled as Gaussian frequency-selective interference channels, wherein each secondary user (SU) competes against the others to maximize his own opportunistic throughput by choosing jointly the sensing duration, the detection thresholds, and the vector power allocation. The proposed general formulation allows to accommodate several (transmit) power and (deterministic/probabilistic) interference constraints, such as constraints on the maximum individual and/or aggregate (probabilistic) interference tolerable at the primary receivers. To keep the optimization as decentralized as possible, global (coupling) interference constraints are imposed by penalizing each SU with a set of time-varying prices based upon his contribution to the total interference; the prices are thus additional variable to optimize. The resulting players' optimization problems are nonconvex; moreover, there are possibly price clearing conditions associated with the global constraints to be satisfied by the solution. All this makes the analysis of the proposed games a challenging task; none of classical results in the game theory literature can be successfully applied. The main contribution of this paper is to develop a novel optimization-based theory for studying the proposed nonconvex games; we provide a comprehensive analysis of the existence and uniqueness of a standard Nash equilibrium, devise alternative best-response based algorithms, and establish their convergence.
The degrees of freedom of the Group Lasso for a General Design
Venue: arXiv cs.IT 2012
Year: 2012

In this paper, we are concerned with regression problems where covariates can be grouped in nonoverlapping blocks, and where only a few of them are assumed to be active. In such a situation, the group Lasso is an at- tractive method for variable selection since it promotes sparsity of the groups. We study the sensitivity of any group Lasso solution to the observations and provide its precise local parameterization. When the noise is Gaussian, this allows us to derive an unbiased estimator of the degrees of freedom of the group Lasso. This result holds true for any fixed design, no matter whether it is under- or overdetermined. With these results at hand, various model selec- tion criteria, such as the Stein Unbiased Risk Estimator (SURE), are readily available which can provide an objectively guided choice of the optimal group Lasso fit.
Domain ontology and multi-criteria analysis for enterprise modeling
Venue: arXiv cs.CY 2012
Year: 2012

Knowing that an enterprise is a complex reality, it is necessary to develop a modeling framework allowing the description of system structure and dynamics that alter the structure. The concept of enterprise modeling addresses this need and many techniques have emerged. Our goal is to provide leaders of Algerian enterprise an overview of modeling techniques. Thus these managers may elect, in collaboration with the University, the modeling technique best suited to their requirements. TWe believe that this could be a step towards an effective reorganization of the enterprise leading. TThis article proposes a domain ontology and multi-criteria analysis in the frame of modeling enterprise. Our approach is based on two stages using the Protégé tool for the technique representation and the PROMETHEE method for their evaluation. The result is a ranking between the different techniques, which allows selecting the most appropriate methodology according to the criteria for a given Tenterprise.