OpenRaiser/Intern-Atlas huggingface dataset:
Learners' Quanta based Design of a Learning Management System
Venue: arXiv cs.OH 2012
Year: 2012

In this paper IEEE Learning Technology System Architecture (LTSA) for LMS software has been analyzed. It has been observed that LTSA is too abstract to be adapted in a uniform way by LMS developers. A Learners' Quanta based high level design that satisfies the IEEE LTSA standard has been proposed for future development of efficient LMS software. A hybrid model of learning fitting into LTSA model has also been proposed while designing.
On the Shape of Curves that are Rational in Polar Coordinates
Venue: arXiv cs.SC 2012
Year: 2012

In this paper we provide a computational approach to the shape of curves which are rational in polar coordinates, i.e. which are defined by means of a parametrization (r(t),θ(t)) where both r(t),θ(t) are rational functions. Our study includes theoretical aspects on the shape of these curves, and algorithmic results which eventually lead to an algorithm for plotting the "interesting parts" of the curve, i.e. the parts showing the main geometrical features of it. On the theoretical side, we prove that these curves, with the exceptions of lines and circles, cannot be algebraic (in cartesian coordinates), we characterize the existence of infinitely many self-intersections, and we connect this with certain phenomena which are not possible in the algebraic world, namely the existence of limit circles, limit points, or spiral branches. On the practical side, we provide an algorithm which has been implemented in the computer algebra system Maple to visualize this kind of curves. Our implementation makes use (and improves some aspects of) the command polarplot currently available in Maple for plotting curves in polar form.
Progress in animation of an EMA-controlled tongue model for acoustic-visual speech synthesis
Venue: arXiv cs.AI 2012
Year: 2012

We present a technique for the animation of a 3D kinematic tongue model, one component of the talking head of an acoustic-visual (AV) speech synthesizer. The skeletal animation approach is adapted to make use of a deformable rig controlled by tongue motion capture data obtained with electromagnetic articulography (EMA), while the tongue surface is extracted from volumetric magnetic resonance imaging (MRI) data. Initial results are shown and future work outlined.
A Pragmatic Coded Modulation Scheme for High-Spectral-Efficiency Fiber-Optic Communications
Venue: arXiv cs.IT 2012
Year: 2012

A pragmatic coded modulation system is presented that incorporates signal shaping and exploits the excellent performance and efficient high-speed decoding architecture of staircase codes. Reliable communication within 0.62 bits/s/Hz of the estimated capacity (per polarization) of a system with L=2000 km is provided by the proposed system, with an error floor below 1E-20. Also, it is shown that digital backpropagation increases the achievable spectral efficiencies---relative to linear equalization---by 0.55 to 0.75 bits/s/Hz per polarization.
Image decomposition with anisotropic diffusion applied to leaf-texture analysis
Venue: arXiv cs.CV 2012
Year: 2012

Texture analysis is an important field of investigation that has received a great deal of interest from computer vision community. In this paper, we propose a novel approach for texture modeling based on partial differential equation (PDE). Each image $f$ is decomposed into a family of derived sub-images. $f$ is split into the $u$ component, obtained with anisotropic diffusion, and the $v$ component which is calculated by the difference between the original image and the $u$ component. After enhancing the texture attribute $v$ of the image, Gabor features are computed as descriptors. We validate the proposed approach on two texture datasets with high variability. We also evaluate our approach on an important real-world application: leaf-texture analysis. Experimental results indicate that our approach can be used to produce higher classification rates and can be successfully employed for different texture applications.
Classification of Binary Self-Dual [48,24,10] Codes with an Automorphism of Odd Prime Order
Venue: arXiv cs.IT 2012
Year: 2012

The purpose of this paper is to complete the classification of binary self-dual [48,24,10] codes with an automorphism of odd prime order. We prove that if there is a self-dual [48, 24, 10] code with an automorphism of type p-(c,f) with p being an odd prime, then p=3, c=16, f=0. By considering only an automorphism of type 3-(16,0), we prove that there are exactly 264 inequivalent self-dual [48, 24, 10] codes with an automorphism of odd prime order, equivalently, there are exactly 264 inequivalent cubic self-dual [48, 24, 10] codes.
Error-Trellis Construction for Tailbiting Convolutional Codes
Venue: arXiv cs.IT 2012
Year: 2012

In this paper, we present an error-trellis construction for tailbiting convolutional codes. A tailbiting error-trellis is characterized by the condition that the syndrome former starts and ends in the same state. We clarify the correspondence between code subtrellises in the tailbiting code-trellis and error subtrellises in the tailbiting error-trellis. Also, we present a construction of tailbiting backward error-trellises. Moreover, we obtain the scalar parity-check matrix for a tailbiting convolutional code. The proposed construction is based on the adjoint-obvious realization of a syndrome former and its behavior is fully used in the discussion.
A System-Level Semantics
Venue: arXiv cs.LO 2012
Year: 2012

Game semantics is a trace-like denotational semantics for programming languages where the notion of legal observable behaviour of a term is defined combinatorially, by means of rules of a game between the term (the "Proponent") and its context (the "Opponent"). In general, the richer the computational features a language has, the less constrained the rules of the semantic game. In this paper we consider the consequences of taking this relaxation of rules to the limit, by granting the Opponent omnipotence, that is, permission to play any move without combinatorial restrictions. However, we impose an epistemic restriction by not granting Opponent omniscience, so that Proponent can have undisclosed secret moves. We introduce a basic C-like programming language and we define such a semantic model for it. We argue that the resulting semantics is an appealingly simple combination of operational and game semantics and we show how certain traces explain system-level attacks, i.e. plausible attacks that are realizable outside of the programming language itself. We also show how allowing Proponent to have secrets ensures that some desirable equivalences in the programming language are preserved.
A new geometric approach to Sturmian words
Venue: arXiv cs.DM 2012
Year: 2012

We introduce a new geometric approach to Sturmian words by means of a mapping that associates certain lines in the n x n -grid and sets of finite Sturmian words of length n. Using this mapping, we give new proofs of the formulas enumerating the finite Sturmian words and the palindromic finite Sturmian words of a given length. We also give a new proof for the well-known result that a factor of a Sturmian word has precisely two return words.
A Multi-Path Certification Protocol for Mobile Ad Hoc Networks
Venue: arXiv cs.CR 2012
Year: 2012

A mobile ad hoc network (MANET) is a collection of autonomous nodes that communicate with each other by forming a multi-hop radio network and maintaining connections in a decentralized manner. Security remains a major challenge for these networks due to their features of open medium, dynamically changing topologies, reliance on cooperative algorithms, absence of centralized monitoring points, and lack of clear lines of defense. Most of the routing protocols for MANETs are thus vulnerable to various types of attacks. For security, these protocols are highly dependent on cryptographic key exchange operations. This paper presents a multi-path certification protocol for efficient and reliable key exchange among the nodes in a MANET. Simulation results have shown the effectiveness and efficiency of the protocol.
Ramified Structural Recursion and Corecursion
Venue: arXiv cs.LO 2012
Year: 2012

We investigate feasible computation over a fairly general notion of data and codata. Specifically, we present a direct Bellantoni-Cook-style normal/safe typed programming formalism, RS1, that expresses feasible structural recursions and corecursions over data and codata specified by polynomial functors. (Lists, streams, finite trees, infinite trees, etc. are all directly definable.) A novel aspect of RS1 is that it embraces structure-sharing as in standard functional-programming implementations. As our data representations use sharing, our implementation of structural recursions are memoized to avoid the possibly exponentially-many repeated subcomputations a naive implementation might perform. We introduce notions of size for representations of data (accounting for sharing) and codata (using ideas from type-2 computational complexity) and establish that type-level 1 RS1-functions have polynomial-bounded runtimes and satisfy a polynomial-time completeness condition. Also, restricting RS1 terms to particular types produces characterizations of some standard complexity classes (e.g., omega-regular languages, linear-space functions) and some less-standard classes (e.g., log-space streams).
Space Shift Keying (SSK-) MIMO with Practical Channel Estimates
Venue: arXiv cs.IT 2012
Year: 2012

In this paper, we study the performance of space modulation for Multiple-Input-Multiple-Output (MIMO) wireless systems with imperfect channel knowledge at the receiver. We focus our attention on two transmission technologies, which are the building blocks of space modulation: i) Space Shift Keying (SSK) modulation; and ii) Time-Orthogonal-Signal-Design (TOSD-) SSK modulation, which is an improved version of SSK modulation providing transmit-diversity. We develop a single-integral closed-form analytical framework to compute the Average Bit Error Probability (ABEP) of a mismatched detector for both SSK and TOSD-SSK modulations. The framework exploits the theory of quadratic-forms in conditional complex Gaussian Random Variables (RVs) along with the Gil-Pelaez inversion theorem. The analytical model is very general and can be used for arbitrary transmit- and receive-antennas, fading distributions, fading spatial correlations, and training pilots. The analytical derivation is substantiated through Monte Carlo simulations, and it is shown, over independent and identically distributed (i.i.d.) Rayleigh fading channels, that SSK modulation is as robust as single-antenna systems to imperfect channel knowledge, and that TOSD-SSK modulation is more robust to channel estimation errors than the Alamouti scheme. Furthermore, it is pointed out that only few training pilots are needed to get reliable enough channel estimates for data detection, and that transmit- and receive-diversity of SSK and TOSD-SSK modulations are preserved even with imperfect channel knowledge.
Finding Endogenously Formed Communities
Venue: arXiv cs.DS 2012
Year: 2012

A central problem in e-commerce is determining overlapping communities among individuals or objects in the absence of external identification or tagging. We address this problem by introducing a framework that captures the notion of communities or clusters determined by the relative affinities among their members. To this end we define what we call an affinity system, which is a set of elements, each with a vector characterizing its preference for all other elements in the set. We define a natural notion of (potentially overlapping) communities in an affinity system, in which the members of a given community collectively prefer each other to anyone else outside the community. Thus these communities are endogenously formed in the affinity system and are "self-determined" or "self-certified" by its members. We provide a tight polynomial bound on the number of self-determined communities as a function of the robustness of the community. We present a polynomial-time algorithm for enumerating these communities. Moreover, we obtain a local algorithm with a strong stochastic performance guarantee that can find a community in time nearly linear in the of size the community. Social networks fit particularly naturally within the affinity system framework -- if we can appropriately extract the affinities from the relatively sparse yet rich information from social networks, our analysis then yields a set of efficient algorithms for enumerating self-determined communities in social networks. In the context of social networks we also connect our analysis with results about $(α,β)$-clusters introduced by Mishra, Schreiber, Stanton, and Tarjan \cite{msst}. In contrast with the polynomial bound we prove on the number of communities in the affinity system model, we show that there exists a family of networks with superpolynomial number of $(α,β)$-clusters.
Real Time Communication Capacity for Data Delivery in Wireless Sensor Networks
Venue: arXiv cs.NI 2012
Year: 2012

Real-time applications are performance critical applications that require bounded service latency. In multi-hop wireless ad-hoc and sensor networks, communication delays are dominant over processing delays. Therefore, to enable real-time applications in such networks, the communication latency must be bounded. In this paper, we derive expressions of real-time capacity that characterize the ability of a network to deliver data on time as well as develop network protocols that achieve this capacity. Real-time capacity expressions are obtained and analyzed for the earliest deadline first, deadline monotonic. This paper presents a treatment of the real-time capacity limits. The limits are derived for two extreme traffic topologies namely, the load balanced topology and the convergecast (i.e., many-to-one) topology. It considers DM and EDF scheduling algorithms, and discusses the implications of the capacity limit expressions.
Interactive Encoding and Decoding Based on Binary LDPC Codes with Syndrome Accumulation
Venue: arXiv cs.IT 2012
Year: 2012

Interactive encoding and decoding based on binary low-density parity-check codes with syndrome accumulation (SA-LDPC-IED) is proposed and investigated. Assume that the source alphabet is $\mathbf{GF}(2)$, and the side information alphabet is finite. It is first demonstrated how to convert any classical universal lossless code $\mathcal{C}_n$ (with block length $n$ and side information available to both the encoder and decoder) into a universal SA-LDPC-IED scheme. It is then shown that with the word error probability approaching 0 sub-exponentially with $n$, the compression rate (including both the forward and backward rates) of the resulting SA-LDPC-IED scheme is upper bounded by a functional of that of $\mathcal{C}_n$, which in turn approaches the compression rate of $\mathcal{C}_n$ for each and every individual sequence pair $(x^n,y^n)$ and the conditional entropy rate $\mathrm{H}(X |Y)$ for any stationary, ergodic source and side information $(X, Y)$ as the average variable node degree $\bar{l}$ of the underlying LDPC code increases without bound. When applied to the class of binary source and side information $(X, Y)$ correlated through a binary symmetrical channel with cross-over probability unknown to both the encoder and decoder, the resulting SA-LDPC-IED scheme can be further simplified, yielding even improved rate performance versus the bit error probability when $\bar{l}$ is not large. Simulation results (coupled with linear time belief propagation decoding) on binary source-side information pairs confirm the theoretic analysis, and further show that the SA-LDPC-IED scheme consistently outperforms the Slepian-Wolf coding scheme based on the same underlying LDPC code. As a by-product, probability bounds involving LDPC established in the course are also interesting on their own and expected to have implications on the performance of LDPC for channel coding as well.
Cross-entropy optimisation of importance sampling parameters for statistical model checking
Venue: arXiv cs.PF 2012
Year: 2012

Statistical model checking avoids the exponential growth of states associated with probabilistic model checking by estimating properties from multiple executions of a system and by giving results within confidence bounds. Rare properties are often very important but pose a particular challenge for simulation-based approaches, hence a key objective under these circumstances is to reduce the number and length of simulations necessary to produce a given level of confidence. Importance sampling is a well-established technique that achieves this, however to maintain the advantages of statistical model checking it is necessary to find good importance sampling distributions without considering the entire state space. Motivated by the above, we present a simple algorithm that uses the notion of cross-entropy to find the optimal parameters for an importance sampling distribution. In contrast to previous work, our algorithm uses a low dimensional vector of parameters to define this distribution and thus avoids the often intractable explicit representation of a transition matrix. We show that our parametrisation leads to a unique optimum and can produce many orders of magnitude improvement in simulation efficiency. We demonstrate the efficacy of our methodology by applying it to models from reliability engineering and biochemistry.
An Authoring System for Editing Lessons in Phonetic English in SMIL3.0
Venue: arXiv cs.MM 2012
Year: 2012

One of the difficulties of teaching English is the prosody, including the stress. French learners have difficulties to encode this information about the word because it is irrelevant for them. Therefore, they have difficulty to produce this stress when they speak that language. Studies in this area have concluded that the dual-coding approach (auditory and visual) of a phonetic phenomenon helps a lot to improve its perception and memorization for novice learners. The aim of our work is to provide English teachers with an authoring named SaCoPh for editing multimedia courses that support this approach. This course is based on a template that fits the educational aspects of phonetics, exploiting the features of version 3.0 of the standard SMIL (Synchronized Multimedia Integration Language) for the publication of this course on the web.
Task-Driven Adaptive Statistical Compressive Sensing of Gaussian Mixture Models
Venue: arXiv cs.CV 2012
Year: 2012

A framework for adaptive and non-adaptive statistical compressive sensing is developed, where a statistical model replaces the standard sparsity model of classical compressive sensing. We propose within this framework optimal task-specific sensing protocols specifically and jointly designed for classification and reconstruction. A two-step adaptive sensing paradigm is developed, where online sensing is applied to detect the signal class in the first step, followed by a reconstruction step adapted to the detected class and the observed samples. The approach is based on information theory, here tailored for Gaussian mixture models (GMMs), where an information-theoretic objective relationship between the sensed signals and a representation of the specific task of interest is maximized. Experimental results using synthetic signals, Landsat satellite attributes, and natural images of different sizes and with different noise levels show the improvements achieved using the proposed framework when compared to more standard sensing protocols. The underlying formulation can be applied beyond GMMs, at the price of higher mathematical and computational complexity.
A toolkit to describe and interactively display three-manifolds embedded in four-space
Venue: arXiv cs.CG 2012
Year: 2012

A data structure and toolkit are presented here that allow for the description and manipulation of mathematical models of three-manifolds and their interactive display from multiple viewpoints via the OpenGL 3D graphics package. The data structure and vector math package can be extended to support an arbitrary number of Euclidean spatial dimensions. A model in 4-space is described by its bounding pure simplicial 3-complex. By intersecting a 3-flat with this 3-manifold, the algorithm will extract the requested closed pure simplicial 2-complex surface enclosing the desired 3D slice. The user can interactively rotate, pan, zoom, and shade arbitrary 3D solid or wire-frame views of the revealed 3D object created by intersection, thus exploring both expected and unexpected symmetries or asymmetries in the world of 3-manifolds in 4-space.
Comparing Methods for segmentation of Microcalcification Clusters in Digitized Mammograms
Venue: arXiv cs.CV 2012
Year: 2012

The appearance of microcalcifications in mammograms is one of the early signs of breast cancer. So, early detection of microcalcification clusters (MCCs) in mammograms can be helpful for cancer diagnosis and better treatment of breast cancer. In this paper a computer method has been proposed to support radiologists in detection MCCs in digital mammography. First, in order to facilitate and improve the detection step, mammogram images have been enhanced with wavelet transformation and morphology operation. Then for segmentation of suspicious MCCs, two methods have been investigated. The considered methods are: adaptive threshold and watershed segmentation. Finally, the detected MCCs areas in different algorithms will be compared to find out which segmentation method is more appropriate for extracting MCCs in mammograms.
A Neuron Based Switch: Application to Low Power Mixed Signal Circuits
Venue: arXiv cs.ET 2012
Year: 2012

Human brain is functionally and physically complex. This 'complexity' can be seen as a result of biological design process involving extensive use of concepts such as modularity and hierarchy. Over the past decade, deeper insights into the functioning of cortical neurons have led to the development of models that can be implemented in hardware. The implementation of biologically inspired spiking neuron networks in silicon can provide solutions to difficult cognitive tasks. The work reported in this paper is an application of a VLSI cortical neuron model for low power design. The VLSI implementation shown in this paper is based on the spike and burst firing pattern of cortex and follows the Izhikevich neuron model. This model is applied to a DC differential amplifier as practical application of power reduction
Implementation of exponential and parametrized algorithms in the AGAPE project
Venue: arXiv cs.DS 2012
Year: 2012

This technical report describes the implementation of exact and parametrized exponential algorithms, developed during the French ANR Agape during 2010-2012. The developed algorithms are distributed under the CeCILL license and have been written in Java using the Jung graph library.
A Comparison Between Data Mining Prediction Algorithms for Fault Detection(Case study: Ahanpishegan co.)
Venue: arXiv cs.LG 2012
Year: 2012

In the current competitive world, industrial companies seek to manufacture products of higher quality which can be achieved by increasing reliability, maintainability and thus the availability of products. On the other hand, improvement in products lifecycle is necessary for achieving high reliability. Typically, maintenance activities are aimed to reduce failures of industrial machinery and minimize the consequences of such failures. So the industrial companies try to improve their efficiency by using different fault detection techniques. One strategy is to process and analyze previous generated data to predict future failures. The purpose of this paper is to detect wasted parts using different data mining algorithms and compare the accuracy of these algorithms. A combination of thermal and physical characteristics has been used and the algorithms were implemented on Ahanpishegan's current data to estimate the availability of its produced parts. Keywords: Data Mining, Fault Detection, Availability, Prediction Algorithms.