OpenRaiser/Intern-Atlas huggingface dataset:
Computing GCRDs of Approximate Differential Polynomials
Venue: arXiv cs.SC 2014
Year: 2014

Differential (Ore) type polynomials with approximate polynomial coefficients are introduced. These provide a useful representation of approximate differential operators with a strong algebraic structure, which has been used successfully in the exact, symbolic, setting. We then present an algorithm for the approximate Greatest Common Right Divisor (GCRD) of two approximate differential polynomials, which intuitively is the differential operator whose solutions are those common to the two inputs operators. More formally, given approximate differential polynomials $f$ and $g$, we show how to find "nearby" polynomials $\widetilde f$ and $\widetilde g$ which have a non-trivial GCRD. Here "nearby" is under a suitably defined norm. The algorithm is a generalization of the SVD-based method of Corless et al. (1995) for the approximate GCD of regular polynomials. We work on an appropriately "linearized" differential Sylvester matrix, to which we apply a block SVD. The algorithm has been implemented in Maple and a demonstration of its robustness is presented.
Identity Management issues in Cloud Computing
Venue: arXiv cs.CR 2014
Year: 2014

Cloud computing is providing a low cost on demand services to the users, omnipresent network,large storage capacity due to these features of cloud computing web applications are moving towards the cloud and due to this migration of the web application,cloud computing platform is raised many issues like privacy, security etc. Privacy issue are major concern for the cloud computing. Privacy is to preserve the sensitive information of the cloud consumer and the major issues to the privacy are unauthorized secondary usage, lack of user control, unclear responsibility. For dealing with these privacy issues Identity management method are used. This paper discusses the privacy issue and different kind of identity management technique that are used for preserving the privacy.
Minimizing Energy Consumption for Cooperative Network and Diversity Coded Sensor Networks
Venue: arXiv cs.NI 2014
Year: 2014

In this paper, we present an approach to minimize the energy consumption of multihop wireless packet networks, while achieving the required level of reliability. We consider networks that use Cooperative Network Coding (CNC), which is a synergistic combination of Cooperative Communications and Network Coding. Our approach is to optimize and balance the use of forward error control, error detection, and retransmissions at the packet level for these networks. Additionally, we introduce Cooperative Diversity Coding (CDC), which is a novel means to code the information packets, with the aim of minimizing the energy consumed for coding operations. The performance of CDC is similar to CNC in terms of the probability of successful reception at the destination and expected number of correctly received information packets at the destination. However, CDC requires less energy at the source node because of its implementation simplicity. Achieving minimal energy consumption, with the required level of reliability is critical for the optimum functioning of many wireless sensor and body area networks. For representative applications, the optimized CDC or CNC network achieves >= 25% energy savings compared to the baseline CNC scheme.
Petri Games: Synthesis of Distributed Systems with Causal Memory
Venue: arXiv cs.LO 2014
Year: 2014

We present a new multiplayer game model for the interaction and the flow of information in a distributed system. The players are tokens on a Petri net. As long as the players move in independent parts of the net, they do not know of each other; when they synchronize at a joint transition, each player gets informed of the causal history of the other player. We show that for Petri games with a single environment player and an arbitrary bounded number of system players, deciding the existence of a safety strategy for the system players is EXPTIME-complete.
Tight Bounds for Complementing Parity Automata
Venue: arXiv cs.FL 2014
Year: 2014

We follow a connection between tight determinisation and complementation and establish a complementation procedure from parity automata to nondeterministic Büchi automata and prove it to be tight up to an $O(n)$ factor, where $n$ is the size of the nondeterministic parity automaton. This factor does not depend on the number of priorities.
Identifying Duplicate and Contradictory Information in Wikipedia
Venue: arXiv cs.IR 2014
Year: 2014

Our study identifies sentences in Wikipedia articles that are either identical or highly similar by applying techniques for near-duplicate detection of web pages. This is accomplished with a MapReduce implementation of minhash to identify clusters of sentences with high Jaccard similarity. We show that these clusters can be categorized into six different types, two of which are particularly interesting: identical sentences quantify the extent to which content in Wikipedia is copied and pasted, and near-duplicate sentences that state contradictory facts point to quality issues in Wikipedia.
A ToolBox for Conservative XML Schema Evolution and Document Adaptation
Venue: arXiv cs.DB 2014
Year: 2014

This paper proposes a set of tools to help dealing with XML database evolution. It aims at establishing a multi-system environment where a global integrated system works in harmony with some local original ones, allowing data translation in both directions and, thus, activities on both levels. To deal with schemas, we propose an algorithm that computes a mapping capable of obtaining a global schema which is a conservative extension of original local schemas. The role of the obtained mapping is then twofold: it ensures schema evolution, via composition and inversion, and it guides the construction of a document translator, allowing automatic data adaptation w.r.t. type evolution. This paper applies, extends and put together some of our previous contributions.
Diffusion of the Adoption of Online Retailing in Saudi Arabia
Venue: arXiv cs.CY 2014
Year: 2014

Despite the fact that Saudi Arabia is a leading producer of oil and natural gas, a member of G-20, has the largest and fastest growth of ICT marketplaces in the Arab region, and is very wealthy, online retailing activities are not progressing at the same speed as its growing ICT marketplace. For this reason, the attitudes of retailers in companies at different stages of e-commerce maturity were investigated to determine what factors are causing this problem. The data collection included two stages: first, interviews with 16 retailers and, then, based on the outcomes of the interviews, a quantitative study designed to test and further explore the qualitative interview findings with a sample of 153 retailers in companies at different stages of e-commerce maturity. The results showed striking differences between retailers as a function of the stage of growth of their companies in regard to factors relating to their perceptions of consumers and to organizational factors. At the same time, the results showed agreement between retailers in companies at different stages in relation to environmental factors. The investigation helped to identify the incentives and barriers for each stage of maturity and makes recommendations of what could be done to help companies move from one stage to the next.
Connectivity of Natura 2000 forest sites in Europe
Venue: arXiv cs.CE 2014
Year: 2014

Background/Purpose: In the context of the European Biodiversity policy, the Green Infrastructure Strategy is one supporting tool to mitigate fragmentation, inter-alia to increase the spatial and functional connectivity between protected and unprotected areas. The Joint Research Centre has developed an integrated model to provide a macro-scale set of indices to evaluate the connectivity of the Natura 2000 network, which forms the backbone of a Green Infrastructure for Europe. The model allows a wide assessment and comparison to be performed across countries in terms of structural (spatially connected or isolated sites) and functional connectivity (least-cost distances between sites influenced by distribution, distance and land cover). Main conclusion: The Natura 2000 network in Europe shows differences among countries in terms of the sizes and numbers of sites, their distribution as well as distances between sites. Connectivity has been assessed on the basis of a 500 m average inter-site distance, roads and intensive land use as barrier effects as well as the presence of "green" corridors. In all countries the Natura 2000 network is mostly made of sites which are not physically connected. Highest functional connectivity values are found for Spain, Slovakia, Romania and Bulgaria. The more natural landscape in Sweden and Finland does not result in high inter-site network connectivity due to large inter-site distances. The distribution of subnets with respect to roads explains the higher share of isolated subnets in Portugal than in Belgium.
Towards designing artificial universes for artificial agents under interaction closure
Venue: arXiv cs.MA 2014
Year: 2014

We are interested in designing artificial universes for artifi- cial agents. We view artificial agents as networks of high- level processes on top of of a low-level detailed-description system. We require that the high-level processes have some intrinsic explanatory power and we introduce an extension of informational closure namely interaction closure to capture this. Then we derive a method to design artificial universes in the form of finite Markov chains which exhibit high-level pro- cesses that satisfy the property of interaction closure. We also investigate control or information transfer which we see as an building block for networks representing artificial agents.
Formal Verification of Medina's Sequence of Polynomials for Approximating Arctangent
Venue: arXiv cs.LO 2014
Year: 2014

The verification of many algorithms for calculating transcendental functions is based on polynomial approximations to these functions, often Taylor series approximations. However, computing and verifying approximations to the arctangent function are very challenging problems, in large part because the Taylor series converges very slowly to arctangent-a 57th-degree polynomial is needed to get three decimal places for arctan(0.95). Medina proposed a series of polynomials that approximate arctangent with far faster convergence-a 7th-degree polynomial is all that is needed to get three decimal places for arctan(0.95). We present in this paper a proof in ACL2(r) of the correctness and convergence rate of this sequence of polynomials. The proof is particularly beautiful, in that it uses many results from real analysis. Some of these necessary results were proven in prior work, but some were proven as part of this effort.
Development of a Translator from LLVM to ACL2
Venue: arXiv cs.PL 2014
Year: 2014

In our current work a library of formally verified software components is to be created, and assembled, using the Low-Level Virtual Machine (LLVM) intermediate form, into subsystems whose top-level assurance relies on the assurance of the individual components. We have thus undertaken a project to build a translator from LLVM to the applicative subset of Common Lisp accepted by the ACL2 theorem prover. Our translator produces executable ACL2 formal models, allowing us to both prove theorems about the translated models as well as validate those models by testing. The resulting models can be translated and certified without user intervention, even for code with loops, thanks to the use of the def::ung macro which allows us to defer the question of termination. Initial measurements of concrete execution for translated LLVM functions indicate that performance is nearly 2.4 million LLVM instructions per second on a typical laptop computer. In this paper we overview the translation process and illustrate the translator's capabilities by way of a concrete example, including both a functional correctness theorem as well as a validation test for that example.
Two-Part Reconstruction with Noisy-Sudocodes
Venue: arXiv cs.IT 2014
Year: 2014

We develop a two-part reconstruction framework for signal recovery in compressed sensing (CS), where a fast algorithm is applied to provide partial recovery in Part 1, and a CS algorithm is applied to complete the residual problem in Part 2. Partitioning the reconstruction process into two complementary parts provides a natural trade-off between runtime and reconstruction quality. To exploit the advantages of the two-part framework, we propose a Noisy-Sudocodes algorithm that performs two-part reconstruction of sparse signals in the presence of measurement noise. Specifically, we design a fast algorithm for Part 1 of Noisy-Sudocodes that identifies the zero coefficients of the input signal from its noisy measurements. Many existing CS algorithms could be applied to Part 2, and we investigate approximate message passing (AMP) and binary iterative hard thresholding (BIHT). For Noisy-Sudocodes with AMP in Part 2, we provide a theoretical analysis that characterizes the trade-off between runtime and reconstruction quality. In a 1-bit CS setting where a new 1-bit quantizer is constructed for Part 1 and BIHT is applied to Part 2, numerical results show that the Noisy-Sudocodes algorithm improves over BIHT in both runtime and reconstruction quality.
Consensus-based In-Network Computation of the PARAFAC Decomposition
Venue: arXiv cs.NA 2014
Year: 2014

In this work, we present a new approach for the distributed computation of the PARAFAC decomposition of a third-order tensor across a network of collaborating nodes. We are interested in the case where the overall data gathered across the network can be modeled as a data tensor admitting an essentially unique PARAFAC decomposition, while each node only observes a sub-tensor with not necessarily enough diversity so that identifiability conditions are not locally fulfilled at each node. In this situation, conventional (centralized) tensor based methods cannot be applied individually at each node. By allowing collaboration between neighboring nodes of the network, we propose distributed versions of the alternating least squares (ALS) and Levenberg-Marquardt (LM) algorithms for the in-network estimation of the factor matrices of a third-order tensor. We assume that one of the factor matrices contains parameters that are local to each node, while the two remaining factor matrices contain global parameters that are common to the whole network. The proposed algorithms combine the estimation of the local factors with an in-network computation of the global factors of the PARAFAC decomposition using average consensus over graphs. They emulate their centralized counterparts in the case of ideal data exchange and ideal consensus computations. The performance of the proposed algorithms are evaluated in both ideal and imperfect cases.
Machine learning approach for text and document mining
Venue: arXiv cs.IR 2014
Year: 2014

Text Categorization (TC), also known as Text Classification, is the task of automatically classifying a set of text documents into different categories from a predefined set. If a document belongs to exactly one of the categories, it is a single-label classification task; otherwise, it is a multi-label classification task. TC uses several tools from Information Retrieval (IR) and Machine Learning (ML) and has received much attention in the last years from both researchers in the academia and industry developers. In this paper, we first categorize the documents using KNN based machine learning approach and then return the most relevant documents.
Separable Cosparse Analysis Operator Learning
Venue: arXiv cs.LG 2014
Year: 2014

The ability of having a sparse representation for a certain class of signals has many applications in data analysis, image processing, and other research fields. Among sparse representations, the cosparse analysis model has recently gained increasing interest. Many signals exhibit a multidimensional structure, e.g. images or three-dimensional MRI scans. Most data analysis and learning algorithms use vectorized signals and thereby do not account for this underlying structure. The drawback of not taking the inherent structure into account is a dramatic increase in computational cost. We propose an algorithm for learning a cosparse Analysis Operator that adheres to the preexisting structure of the data, and thus allows for a very efficient implementation. This is achieved by enforcing a separable structure on the learned operator. Our learning algorithm is able to deal with multidimensional data of arbitrary order. We evaluate our method on volumetric data at the example of three-dimensional MRI scans.
Smooth Parametrizations in Dynamics, Analysis, Diophantine and Computational Geometry
Venue: arXiv cs.CG 2014
Year: 2014

Smooth parametrization consists in a subdivision of the mathematical objects under consideration into simple pieces, and then parametric representation of each piece, while keeping control of high order derivatives. The main goal of the present paper is to provide a short overview of some results and open problems on smooth parametrization and its applications in several apparently rather separated domains: Smooth Dynamics, Diophantine Geometry, Approximation Theory, and Computational Geometry. The structure of the results, open problems, and conjectures in each of these domains shows in many cases a remarkable similarity, which we try to stress. Sometimes this similarity can be easily explained, sometimes the reasons remain somewhat obscure, and it motivates some natural questions discussed in the paper. We present also some new results, stressing interconnection between various types and various applications of smooth parametrization.
MIMO In Vivo
Venue: arXiv cs.IT 2014
Year: 2014

We present the performance of MIMO for in vivo environments, using ANSYS HFSS and their complete human body model, to determine the maximum data rates that can be achieved using an IEEE 802.11n system. Due to the lossy nature of the in vivo medium, achieving high data rates with reliable performance will be a challenge, especially since the in vivo antenna performance is strongly affected by near field coupling to the lossy medium and the signals levels will be limited by specified specific absorption rate (SAR) levels. We analyzed the bit error rate (BER) of a MIMO system with one pair of antennas placed in vivo and the second pair placed inside and outside the body at various distances from the in vivo antennas. The results were compared to SISO simulations and showed that by using MIMO in vivo, significant performance gain can be achieved, and at least two times the data rate can be supported with SAR limited transmit power levels, making it possible to achieve target data rates in the 100 Mbps.
Security Requirements, Counterattacks and Projects in Healthcare Applications Using WSNs - A Review
Venue: arXiv cs.CR 2014
Year: 2014

Healthcare applications are well thought-out as interesting fields for WSN where patients can be examine using wireless medical sensor networks. Inside the hospital or extensive care surroundings there is a tempting need for steady monitoring of essential body functions and support for patient mobility. Recent research cantered on patient reliable communication, mobility, and energy-efficient routing. Yet deploying new expertise in healthcare applications presents some understandable security concerns which are the important concern in the inclusive deployment of wireless patient monitoring systems. This manuscript presents a survey of the security features, its counter attacks in healthcare applications including some proposed projects which have been done recently.
Toward verbalizing ontologies in isiZulu
Venue: arXiv cs.CL 2014
Year: 2014

IsiZulu is one of the eleven official languages of South Africa and roughly half the population can speak it. It is the first (home) language for over 10 million people in South Africa. Only a few computational resources exist for isiZulu and its related Nguni languages, yet the imperative for tool development exists. We focus on natural language generation, and the grammar options and preferences in particular, which will inform verbalization of knowledge representation languages and could contribute to machine translation. The verbalization pattern specification shows that the grammar rules are elaborate and there are several options of which one may have preference. We devised verbalization patterns for subsumption, basic disjointness, existential and universal quantification, and conjunction. This was evaluated in a survey among linguists and non-linguists. Some differences between linguists and non-linguists can be observed, with the former much more in agreement, and preferences depend on the overall structure of the sentence, such as singular for subsumption and plural in other cases.
Introduction to Neutrosophic Statistics
Venue: arXiv cs.AI 2014
Year: 2014

Neutrosophic Statistics means statistical analysis of population or sample that has indeterminate (imprecise, ambiguous, vague, incomplete, unknown) data. For example, the population or sample size might not be exactly determinate because of some individuals that partially belong to the population or sample, and partially they do not belong, or individuals whose appurtenance is completely unknown. Also, there are population or sample individuals whose data could be indeterminate. In this book, we develop the 1995 notion of neutrosophic statistics. We present various practical examples. It is possible to define the neutrosophic statistics in many ways, because there are various types of indeterminacies, depending on the problem to solve.
Slime Mould Logic Gates Based on Frequency Changes of Electrical Potential Oscillation
Venue: arXiv cs.ET 2014
Year: 2014

Physarum polycephalum is a large single amoeba cell, which in its plasmodial phase,forages and connects nearby food sources with protoplasmic tubes. The organism forages for food by growing these tubes towards detected food stuffs, this foraging behaviour is governed by simple rules of photoavoidance and chemotaxis. The electrical activity of the tubes oscillates, creating a peristaltic like action within the tubes, forcing cytoplasm along the lumen; the frequency of this oscillation controls the speed and direction of growth. External stimuli such as light and food cause changes in the oscillation frequency. We demonstrate that using these stimuli as logical inputs we can approximate logic gates using these tubes and derive combinational logic circuits by cascading the gates, with software analysis providing the output of each gate and determining the input of the following gate. Basic gates OR, AND and NOT were correct 90%, 77.8% and 91.7% of the time respectively. Derived logic circuits XOR, Half Adder and Full Adder were 70.8%, 65% and 58.8% accurate respectively. Accuracy of the combinational logic decreases as the number of gates is increased, however they are at least as accurate as previous logic approximations using spatial growth of Physarum polycephalum and up to 30 times as fast at computing the logical output. The results shown here demonstrate a significant advancement in organism-based computing, providing a solid basis for hybrid computers of the future.
Monad Transformers for Backtracking Search
Venue: arXiv cs.PL 2014
Year: 2014

This paper extends Escardo and Oliva's selection monad to the selection monad transformer, a general monadic framework for expressing backtracking search algorithms in Haskell. The use of the closely related continuation monad transformer for similar purposes is also discussed, including an implementation of a DPLL-like SAT solver with no explicit recursion. Continuing a line of work exploring connections between selection functions and game theory, we use the selection monad transformer with the nondeterminism monad to obtain an intuitive notion of backward induction for a certain class of nondeterministic games.