OpenRaiser/Intern-Atlas huggingface dataset:
Experiences with Automated Build and Test for Geodynamics Simulation Codes
Venue: arXiv cs.CE 2013
Year: 2013

The Computational Infrastructure for Geodynamics (CIG) is an NSF funded project that develops, supports, and disseminates community-accessible software for the geodynamics research community. CIG software supports a variety of computational geodynamic research from mantle and core dynamics, to crustal and earthquake dynamics, to magma migration and seismology. To support this type of project a backend computational infrastructure is necessary. Part of this backend infrastructure is an automated build and testing system to ensure codes and changes to them are compatible with multiple platforms and that the changes do not significantly affect the scientific results. In this paper we describe the build and test infrastructure for CIG based on the BaTLab system, how it is organized, and how it assists in operations. We demonstrate the use of this type of testing for a suite of geophysics codes, show why codes may compile on one platform but not on another, and demonstrate how minor changes may alter the computed results in unexpected ways that can influence the scientific interpretation. Finally, we examine result comparison between platforms and show how the compiler or operating system may affect results.
One-dimensional Array Grammars and P Systems with Array Insertion and Deletion Rules
Venue: arXiv cs.FL 2013
Year: 2013

We consider the (one-dimensional) array counterpart of contextual as well as insertion and deletion string grammars and consider the operations of array insertion and deletion in array grammars. First we show that the emptiness problem for P systems with (one-dimensional) insertion rules is undecidable. Then we show computational completeness of P systems using (one-dimensional) array insertion and deletion rules even of norm one only. The main result of the paper exhibits computational completeness of one-dimensional array grammars using array insertion and deletion rules of norm at most two.
Automated Password Extraction Attack on Modern Password Managers
Venue: arXiv cs.CR 2013
Year: 2013

To encourage users to use stronger and more secure passwords, modern web browsers offer users password management services, allowing users to save previously entered passwords locally onto their hard drives. We present Lupin, a tool that automatically extracts these saved passwords without the user's knowledge. Lupin allows a network adversary to obtain passwords as long as the login form appears on a non-HTTPS page. Unlike existing password sniffing tools, Lupin can obtain passwords for websites users are not visiting. Furthermore, Lupin can extract passwords embedded in login forms with a destination address served in HTTPS. To determine the number of websites vulnerable to our attack, we crawled the top 45,000 most popular websites from Alexa's top website list and discovered that at least 28% of these sites are vulnerable. To further demonstrate the feasibility of our attack, we tested Lupin under controlled conditions using one of the authors' computers. Lupin was able to extract passwords from 1,000 websites in less than 35 seconds. We suggest techniques for web developers to protect their web applications from attack, and we propose alternative designs for a secure password manager.
Accelerating Hessian-free optimization for deep neural networks by implicit preconditioning and sampling
Venue: arXiv cs.LG 2013
Year: 2013

Hessian-free training has become a popular parallel second or- der optimization technique for Deep Neural Network training. This study aims at speeding up Hessian-free training, both by means of decreasing the amount of data used for training, as well as through reduction of the number of Krylov subspace solver iterations used for implicit estimation of the Hessian. In this paper, we develop an L-BFGS based preconditioning scheme that avoids the need to access the Hessian explicitly. Since L-BFGS cannot be regarded as a fixed-point iteration, we further propose the employment of flexible Krylov subspace solvers that retain the desired theoretical convergence guarantees of their conventional counterparts. Second, we propose a new sampling algorithm, which geometrically increases the amount of data utilized for gradient and Krylov subspace iteration calculations. On a 50-hr English Broadcast News task, we find that these methodologies provide roughly a 1.5x speed-up, whereas, on a 300-hr Switchboard task, these techniques provide over a 2.3x speedup, with no loss in WER. These results suggest that even further speed-up is expected, as problems scale and complexity grows.
Nano-scale reservoir computing
Venue: arXiv cs.ET 2013
Year: 2013

This work describes preliminary steps towards nano-scale reservoir computing using quantum dots. Our research has focused on the development of an accumulator-based sensing system that reacts to changes in the environment, as well as the development of a software simulation. The investigated systems generate nonlinear responses to inputs that make them suitable for a physical implementation of a neural network. This development will enable miniaturisation of the neurons to the molecular level, leading to a range of applications including monitoring of changes in materials or structures. The system is based around the optical properties of quantum dots. The paper will report on experimental work on systems using Cadmium Selenide (CdSe) quantum dots and on the various methods to render the systems sensitive to pH, redox potential or specific ion concentration. Once the quantum dot-based systems are rendered sensitive to these triggers they can provide a distributed array that can monitor and transmit information on changes within the material.
Projection onto the probability simplex: An efficient algorithm with a simple proof, and an application
Venue: arXiv cs.LG 2013
Year: 2013

We provide an elementary proof of a simple, efficient algorithm for computing the Euclidean projection of a point onto the probability simplex. We also show an application in Laplacian K-modes clustering.
Large induced subgraphs via triangulations and CMSO
Venue: arXiv cs.DS 2013
Year: 2013

We obtain an algorithmic meta-theorem for the following optimization problem. Let ϕ be a Counting Monadic Second Order Logic (CMSO) formula and t be an integer. For a given graph G, the task is to maximize |X| subject to the following: there is a set of vertices F of G, containing X, such that the subgraph G[F] induced by F is of treewidth at most t, and structure (G[F],X) models ϕ. Some special cases of this optimization problem are the following generic examples. Each of these cases contains various problems as a special subcase: 1) "Maximum induced subgraph with at most l copies of cycles of length 0 modulo m", where for fixed nonnegative integers m and l, the task is to find a maximum induced subgraph of a given graph with at most l vertex-disjoint cycles of length 0 modulo m. 2) "Minimum Γ-deletion", where for a fixed finite set of graphs Γ containing a planar graph, the task is to find a maximum induced subgraph of a given graph containing no graph from Γ as a minor. 3) "Independent Π-packing", where for a fixed finite set of connected graphs Π, the task is to find an induced subgraph G[F] of a given graph G with the maximum number of connected components, such that each connected component of G[F] is isomorphic to some graph from Π. We give an algorithm solving the optimization problem on an n-vertex graph G in time O(#pmc n^{t+4} f(t,ϕ)), where #pmc is the number of all potential maximal cliques in G and f is a function depending of t and ϕ only. We also show how a similar running time can be obtained for the weighted version of the problem. Pipelined with known bounds on the number of potential maximal cliques, we deduce that our optimization problem can be solved in time O(1.7347^n) for arbitrary graphs, and in polynomial time for graph classes with polynomial number of minimal separators.
A New Method to Compute the 2-adic Complexity of Binary Sequences
Venue: arXiv cs.CR 2013
Year: 2013

In this paper, a new method is presented to compute the 2-adic complexity of pseudo-random sequences. With this method, the 2-adic complexities of all the known sequences with ideal 2-level autocorrelation are uniformly determined. Results show that their 2-adic complexities equal their periods. In other words, their 2-adic complexities attain the maximum. Moreover, 2-adic complexities of two classes of optimal autocorrelation sequences with period $N\equiv1\mod4$, namely Legendre sequences and Ding-Helleseth-Lam sequences, are investigated. Besides, this method also can be used to compute the linear complexity of binary sequences regarded as sequences over other finite fields.
Throughput Maximization in the Speed-Scaling Setting
Venue: arXiv cs.DS 2013
Year: 2013

We are given a set of $n$ jobs and a single processor that can vary its speed dynamically. Each job $J_j$ is characterized by its processing requirement (work) $p_j$, its release date $r_j$ and its deadline $d_j$. We are also given a budget of energy $E$ and we study the scheduling problem of maximizing the throughput (i.e. the number of jobs which are completed on time). We propose a dynamic programming algorithm that solves the preemptive case of the problem, i.e. when the execution of the jobs may be interrupted and resumed later, in pseudo-polynomial time. Our algorithm can be adapted for solving the weighted version of the problem where every job is associated with a weight $w_j$ and the objective is the maximization of the sum of the weights of the jobs that are completed on time. Moreover, we provide a strongly polynomial time algorithm to solve the non-preemptive unweighed case when the jobs have the same processing requirements. For the weighted case, our algorithm can be adapted for solving the non-preemptive version of the problem in pseudo-polynomial time.
Finding role communities in directed networks using Role-Based Similarity, Markov Stability and the Relaxed Minimum Spanning Tree
Venue: arXiv cs.SI 2013
Year: 2013

We present a framework to cluster nodes in directed networks according to their roles by combining Role-Based Similarity (RBS) and Markov Stability, two techniques based on flows. First we compute the RBS matrix, which contains the pairwise similarities between nodes according to the scaled number of in- and out-directed paths of different lengths. The weighted RBS similarity matrix is then transformed into an undirected similarity network using the Relaxed Minimum-Spanning Tree (RMST) algorithm, which uses the geometric structure of the RBS matrix to unblur the network, such that edges between nodes with high, direct RBS are preserved. Finally, we partition the RMST similarity network into role-communities of nodes at all scales using Markov Stability to find a robust set of roles in the network. We showcase our framework through a biological and a man-made network.
Initial Findings from a Study of Best Practices and Models for Cyberinfrastructure Software Sustainability
Venue: arXiv cs.SE 2013
Year: 2013

We present a set of common themes and recommendations extracted from in depth interviews with the leaders of 12 distinct cyberinfrastructure software projects. These interviews were conducted as part of a larger study to identify and elucidate the best practices and management models that lead to sustainability for cyberinfrastructure software. Respondents in a formal survey of cyberinfrastructure users identified these projects as good examples of sustained software initiatives. While there is clearly no single method or plan that will guarantee sustainability for all projects, we can draw general guidance from these exemplars. This paper presents the common themes, ideas, and recommendations that emerged from those interviews.
Zahir: a Object-Oriented Framework for Computer Graphics
Venue: arXiv cs.GR 2013
Year: 2013

In this article we present Zahir, a framework for experimentation in Computer Graphics that provides a group of object-oriented base components that take care of common tasks in rendering techniques and algorithms, specially those of Non Photo-realistic Rendering (NPR). These components allow developers to implement rendering techniques and algorithms over static and animated meshes. Currently, Zahir is being used in a Master's Thesis and as support material in the undergraduate Computer Graphics course in University of Chile.
Memory transfer optimization for a lattice Boltzmann solver on Kepler architecture nVidia GPUs
Venue: arXiv cs.DC 2013
Year: 2013

The Lattice Boltzmann method (LBM) for solving fluid flow is naturally well suited to an efficient implementation for massively parallel computing, due to the prevalence of local operations in the algorithm. This paper presents and analyses the performance of a 3D lattice Boltzmann solver, optimized for third generation nVidia GPU hardware, also known as `Kepler'. We provide a review of previous optimisation strategies and analyse data read/write times for different memory types. In LBM, the time propagation step (known as streaming), involves shifting data to adjacent locations and is central to parallel performance; here we examine three approaches which make use of different hardware options. Two of which make use of `performance enhancing' features of the GPU; shared memory and the new shuffle instruction found in Kepler based GPUs. These are compared to a standard transfer of data which relies instead on optimised storage to increase coalesced access. It is shown that the more simple approach is most efficient; since the need for large numbers of registers per thread in LBM limits the block size and thus the efficiency of these special features is reduced. Detailed results are obtained for a D3Q19 LBM solver, which is benchmarked on nVidia K5000M and K20C GPUs. In the latter case the use of a read-only data cache is explored, and peak performance of over 1036 Million Lattice Updates Per Second (MLUPS) is achieved. The appearance of a periodic bottleneck in the solver performance is also reported, believed to be hardware related; spikes in iteration-time occur with a frequency of around 11Hz for both GPUs, independent of the size of the problem.
Structure Learning of Probabilistic Logic Programs by Searching the Clause Space
Venue: arXiv cs.LG 2013
Year: 2013

Learning probabilistic logic programming languages is receiving an increasing attention and systems are available for learning the parameters (PRISM, LeProbLog, LFI-ProbLog and EMBLEM) or both the structure and the parameters (SEM-CP-logic and SLIPCASE) of these languages. In this paper we present the algorithm SLIPCOVER for "Structure LearnIng of Probabilistic logic programs by searChing OVER the clause space". It performs a beam search in the space of probabilistic clauses and a greedy search in the space of theories, using the log likelihood of the data as the guiding heuristics. To estimate the log likelihood SLIPCOVER performs Expectation Maximization with EMBLEM. The algorithm has been tested on five real world datasets and compared with SLIPCASE, SEM-CP-logic, Aleph and two algorithms for learning Markov Logic Networks (Learning using Structural Motifs (LSM) and ALEPH++ExactL1). SLIPCOVER achieves higher areas under the precision-recall and ROC curves in most cases.
High-level programming and control for industrial robotics: using a hand-held accelerometer-based input device for gesture and posture recognition
Venue: arXiv cs.RO 2013
Year: 2013

Purpose - Most industrial robots are still programmed using the typical teaching process, through the use of the robot teach pendant. This is a tedious and time-consuming task that requires some technical expertise, and hence new approaches to robot programming are required. The purpose of this paper is to present a robotic system that allows users to instruct and program a robot with a high-level of abstraction from the robot language. Design/methodology/approach - The paper presents in detail a robotic system that allows users, especially non-expert programmers, to instruct and program a robot just showing it what it should do, in an intuitive way. This is done using the two most natural human interfaces (gestures and speech), a force control system and several code generation techniques. Special attention will be given to the recognition of gestures, where the data extracted from a motion sensor (three-axis accelerometer) embedded in the Wii remote controller was used to capture human hand behaviours. Gestures (dynamic hand positions) as well as manual postures (static hand positions) are recognized using a statistical approach and artificial neural networks. Practical implications - The key contribution of this paper is that it offers a practical method to program robots by means of gestures and speech, improving work efficiency and saving time. Originality/value - This paper presents an alternative to the typical robot teaching process, extending the concept of human-robot interaction and co-worker scenario. Since most companies do not have engineering resources to make changes or add new functionalities to their robotic manufacturing systems, this system constitutes a major advantage for small- to medium-sized enterprises.
Puzzle Encryption Algorithm
Venue: arXiv cs.CR 2013
Year: 2013

This document describes the symmetric encryption algorithm called Puzzle. It is free and open. The objective of this paper is to get an opinion about its security from the cryptology community. It is separated in two parts, a technical description of the algorithm and its cryptanalysis. The algorithm has some interesting properties : The block size is variable and unknown from an attacker. The size of the key has no limit and is unknown from an attacker. The key size does not affect the algorithm speed (using a 256 bit key is the same as using a 1024 bit key). The algorithm is much faster than the average cryptographic function. Experimental test showed 600 Mo/s - 4 cycles/byte on an Intel Core 2 Duo P8600 2.40GHz and 1,2 Go/s - 2 cycles/byte on an Intel i5-3210M 2.50GHz. Both CPU had only 2 cores.
Rôle communautaire des capitalistes sociaux dans Twitter
Venue: arXiv cs.CY 2013
Year: 2013

Les capitalistes sociaux sont des utilisateurs de médias sociaux tels que Twitter, appliquant diverses techniques pour obtenir un maximum de visibilité. Ils peuvent être néfastes à l'équilibre du service, dans la mesure où leurs comptes, en gagnant en importance sans réelle raison de contenu, rendent difficile l'accès à un contenu pertinent. Dans ce travail, nous nous intéressons à leur caractérisation d'un point de vue purement topologique, i.e. sans considérer la nature des contenus partagés. Nous utilisons pour cela la notion de rôle communautaire, qui est basée sur la structure de communautés du réseau étudié. Nous apportons des modifications à des mesures précédemment définies à cet effet, et proposons une méthode objective de détection des rôles. Nous appliquons ensuite notre méthode à l'analyse d'un réseau représentant Twitter. Nos résultats montrent que les rôles que nous identifions via nos mesures se révèlent particulièrement cohérents par rapport aux capitalistes sociaux du réseau Twitter, dont le comportement est clairement identifié---Social capitalists are social media users taking advantage of various methods to maximize their visibility. This results in artificially important accounts, in the sense this importance is not backed by any real content. The risk is then to see those accounts hiding relevant contents and therefore preventing other users to access them. In this work, we want to characterize social capitalists from a purely topological perspective, i.e. without considering the nature of the shared contents. For this purpose, we use the notion of community role, based on the community structure of the studied network. We modify some measures previously designed for this matter, and propose an objective method to determine roles. We then apply this method to the analysis of a Twitter network. Our results show the roles identified through our measures are particularly consistent with Twitter's social capitalists, whose behavior was clearly identified.
Square-Free Shuffles of Words
Venue: arXiv cs.DM 2013
Year: 2013

Let $u \shuffle v$ denote the set of all shuffles of the words $u$ and $v$. It is shown that for each integer $n \geq 3$ there exists a square-free ternary word $u$ of length $n$ such that $u\shuffle u$ contains a square-free word. This property is then shown to also hold for infinite words, i.e., there exists an infinite square-free word $u$ on three letters such that $u$ can be shuffled with itself to produce an infinite square-free word $w \in u \shuffle u$.
COSMOS A Context Sensitive Model For Dynamic Configuration Of Smartphones Using Multifactor Analysis
Venue: arXiv cs.HC 2013
Year: 2013

With the prolific growth in usage of smartphones across the spectrum of people in the society it becomes mandatory to handle and configure these devices effectively to achieve optimum results from it. This paper proposes a context sensitive model termed COSMOS (COntext Sensitive MOdel for Smartphones) for configuring the smartphones using multifactor analysis with the help of decision trees. The COSMOS model proposed in this paper facilitates the configuration of various smartphone settings implicitly based on the user's current context, without interrupting the user for various inputs. The COSMOS model also proposes multiple context parameters like location, scheduler data, recent call log settings etc to decide the appropriate settings for the smartphones. The proposed model is validated by a prototype implementation in the Android platform. Various tests were conducted in the implementation and the settings relevancy metric value of 90.95% confirms the efficiency of the proposed model.
Application of Artificial Neural Networks in Estimating Participation in Elections
Venue: arXiv cs.NE 2013
Year: 2013

It is approved that artificial neural networks can be considerable effective in anticipating and analyzing flows in which traditional methods and statics are not able to solve. in this article, by using two-layer feedforward network with tan-sigmoid transmission function in input and output layers, we can anticipate participation rate of public in kohgiloye and boyerahmad province in future presidential election of islamic republic of iran with 91% accuracy. the assessment standards of participation such as confusion matrix and roc diagrams have been approved our claims.
A Search Algorithm to Find Multiple Sets of One Dimensional Unipolar (Optical) Orthogonal Codes with Same Code-length and Low Weight
Venue: arXiv cs.IT 2013
Year: 2013

This paper describes a search algorithm to find multiple sets of one dimensional unipolar (optical) orthogonal codes characterized by parameters, binary code sequence of length (n bits) and weight w (number of bit 1s in the sequence) as well as auto-correlation and cross-correlation constraint respectively for the codes within a set. For a given code length n and code weight w all possible difference sets, with auto-correlation constraints lying from 1 to w-1 can be designed with distinct code serial number. For given cross-correlation constraint from 1 to w-1 Multiple sets can be searched out of the codes with auto-correlation constraints less than or equal to given auto-correlation constraint using proposed algorithm. The searched multiple sets can be sorted as having number of codes not less than the upper bound of the sets given by Johnson bound. These one dimensional unipolar orthogonal codes have their application in incoherent optical code division multiple access systems.