OpenRaiser/Intern-Atlas huggingface dataset:
Hierarchical Graphical Models for Multigroup Shape Analysis using Expectation Maximization with Sampling in Kendall's Shape Space
Venue: arXiv cs.CV 2013
Year: 2013

This paper proposes a novel framework for multi-group shape analysis relying on a hierarchical graphical statistical model on shapes within a population.The framework represents individual shapes as point setsmodulo translation, rotation, and scale, following the notion in Kendall shape space.While individual shapes are derived from their group shape model, each group shape model is derived from a single population shape model. The hierarchical model follows the natural organization of population data and the top level in the hierarchy provides a common frame of reference for multigroup shape analysis, e.g. classification and hypothesis testing. Unlike typical shape-modeling approaches, the proposed model is a generative model that defines a joint distribution of object-boundary data and the shape-model variables. Furthermore, it naturally enforces optimal correspondences during the process of model fitting and thereby subsumes the so-called correspondence problem. The proposed inference scheme employs an expectation maximization (EM) algorithm that treats the individual and group shape variables as hidden random variables and integrates them out before estimating the parameters (population mean and variance and the group variances). The underpinning of the EM algorithm is the sampling of pointsets, in Kendall shape space, from their posterior distribution, for which we exploit a highly-efficient scheme based on Hamiltonian Monte Carlo simulation. Experiments in this paper use the fitted hierarchical model to perform (1) hypothesis testing for comparison between pairs of groups using permutation testing and (2) classification for image retrieval. The paper validates the proposed framework on simulated data and demonstrates results on real data.
Improving problem solving by exploiting the concept of symmetry
Venue: arXiv cs.AI 2013
Year: 2013

We investigate the concept of symmetry and its role in problem solving. This paper first defines precisely the elements that constitute a "problem" and its "solution," and gives several examples to illustrate these definitions. Given precise definitions of problems, it is relatively straightforward to construct a search process for finding solutions. Finally this paper attempts to exploit the concept of symmetry in improving problem solving.
High-SNR Asymptotics of Mutual Information for Discrete Constellations with Applications to BICM
Venue: arXiv cs.IT 2013
Year: 2013

Asymptotic expressions of the mutual information between any discrete input and the corresponding output of the scalar additive white Gaussian noise channel are presented in the limit as the signal-to-noise ratio (SNR) tends to infinity. Asymptotic expressions of the symbol-error probability (SEP) and the minimum mean-square error (MMSE) achieved by estimating the channel input given the channel output are also developed. It is shown that for any input distribution, the conditional entropy of the channel input given the output, MMSE and SEP have an asymptotic behavior proportional to the Gaussian Q-function. The argument of the Q-function depends only on the minimum Euclidean distance (MED) of the constellation and the SNR, and the proportionality constants are functions of the MED and the probabilities of the pairs of constellation points at MED. The developed expressions are then generalized to study the high-SNR behavior of the generalized mutual information (GMI) for bit-interleaved coded modulation (BICM). By means of these asymptotic expressions, the long-standing conjecture that Gray codes are the binary labelings that maximize the BICM-GMI at high SNR is proven. It is further shown that for any equally spaced constellation whose size is a power of two, there always exists an anti-Gray code giving the lowest BICM-GMI at high SNR.
Blind Multilinear Identification
Venue: arXiv cs.IT 2013
Year: 2013

We discuss a technique that allows blind recovery of signals or blind identification of mixtures in instances where such recovery or identification were previously thought to be impossible: (i) closely located or highly correlated sources in antenna array processing, (ii) highly correlated spreading codes in CDMA radio communication, (iii) nearly dependent spectra in fluorescent spectroscopy. This has important implications --- in the case of antenna array processing, it allows for joint localization and extraction of multiple sources from the measurement of a noisy mixture recorded on multiple sensors in an entirely deterministic manner. In the case of CDMA, it allows the possibility of having a number of users larger than the spreading gain. In the case of fluorescent spectroscopy, it allows for detection of nearly identical chemical constituents. The proposed technique involves the solution of a bounded coherence low-rank multilinear approximation problem. We show that bounded coherence allows us to establish existence and uniqueness of the recovered solution. We will provide some statistical motivation for the approximation problem and discuss greedy approximation bounds. To provide the theoretical underpinnings for this technique, we develop a corresponding theory of sparse separable decompositions of functions, including notions of rank and nuclear norm that specialize to the usual ones for matrices and operators but apply to also hypermatrices and tensors.
Nonsymmetric multigrid preconditioning for conjugate gradient methods
Venue: arXiv cs.NA 2013
Year: 2013

We numerically analyze the possibility of turning off post-smoothing (relaxation) in geometric multigrid when used as a preconditioner in conjugate gradient linear and eigenvalue solvers for the 3D Laplacian. The geometric Semicoarsening Multigrid (SMG) method is provided by the hypre parallel software package. We solve linear systems using two variants (standard and flexible) of the preconditioned conjugate gradient (PCG) and preconditioned steepest descent (PSD) methods. The eigenvalue problems are solved using the locally optimal block preconditioned conjugate gradient (LOBPCG) method available in hypre through BLOPEX software. We observe that turning off the post-smoothing in SMG dramatically slows down the standard PCG-SMG. For flexible PCG and LOBPCG, our numerical results show that post-smoothing can be avoided, resulting in overall acceleration, due to the high costs of smoothing and relatively insignificant decrease in convergence speed. We numerically demonstrate for linear systems that PSD-SMG and flexible PCG-SMG converge similarly if SMG post-smoothing is off. We experimentally show that the effect of acceleration is independent of memory interconnection. A theoretical justification is provided.
Model Checking with Program Slicing Based on Variable Dependence Graphs
Venue: arXiv cs.LO 2013
Year: 2013

In embedded control systems, the potential risks of software defects have been increasing because of software complexity which leads to, for example, timing related problems. These defects are rarely found by tests or simulations. To detect such defects, we propose a modeling method which can generate software models for model checking with a program slicing technique based on a variable dependence graph. We have applied the proposed method to one case in automotive control software and demonstrated the effectiveness of the method. Furthermore, we developed a software tool to automate model generation and achieved a 35% decrease in total verification time on model checking.
Generating High-Order Threshold Functions with Multiple Thresholds
Venue: arXiv cs.NE 2013
Year: 2013

In this paper, we consider situations in which a given logical function is realized by a multithreshold threshold function. In such situations, constant functions can be easily obtained from multithreshold threshold functions, and therefore, we can show that it becomes possible to optimize a class of high-order neural networks. We begin by proposing a generating method for threshold functions in which we use a vector that determines the boundary between the linearly separable function and the high-order threshold function. By applying this method to high-order threshold functions, we show that functions with the same weight as, but a different threshold than, a threshold function generated by the generation process can be easily obtained. We also show that the order of the entire network can be extended while maintaining the structure of given functions.
Set-Membership Adaptive Algorithms based on Time-Varying Error Bounds for Interference Suppression
Venue: arXiv cs.IT 2013
Year: 2013

This work presents set-membership adaptive algorithms based on time-varying error bounds for CDMA interference suppression. We introduce a modified family of set-membership adaptive algorithms for parameter estimation with time-varying error bounds. The algorithms considered include modified versions of the set-membership normalized least mean squares (SM-NLMS), the affine projection (SM-AP) and the bounding ellipsoidal adaptive constrained (BEACON) recursive least-squares technique. The important issue of error bound specification is addressed in a new framework that takes into account parameter estimation dependency, multi-access and inter-symbol interference for DS-CDMA communications. An algorithm for tracking and estimating the interference power is proposed and analyzed. This algorithm is then incorporated into the proposed time-varying error bound mechanisms. Computer simulations show that the proposed algorithms are capable of outperforming previously reported techniques with a significantly lower number of parameter updates and a reduced risk of overbounding or underbounding.
Binary Tree Arithmetic with Generalized Constructors
Venue: arXiv cs.MS 2013
Year: 2013

We describe arithmetic computations in terms of operations on some well known free algebras (S1S, S2S and ordered rooted binary trees) while emphasizing the common structure present in all them when seen as isomorphic with the set of natural numbers. Constructors and deconstructors seen through an initial algebra semantics are generalized to recursively defined functions obeying similar laws. Implementation using Scala's apply and unapply are discussed together with an application to a realistic arbitrary size arithmetic package written in Scala, based on the free algebra of rooted ordered binary trees, which also supports rational number operations through an extension to signed rationals of the Calkin-Wilf bijection.
Knowledge Discovery System For Fiber Reinforced Polymer Matrix Composite Laminate
Venue: arXiv cs.AI 2013
Year: 2013

In this paper Knowledge Discovery System (KDS) is proposed and implemented for the extraction of knowledge-mean stiffness of a polymer composite material in which when fibers are placed at different orientations. Cosine amplitude method is implemented for retrieving compatible polymer matrix and reinforcement fiber which is coming under predicted fiber class, from the polymer and reinforcement database respectively, based on the design requirements. Fuzzy classification rules to classify fibers into short, medium and long fiber classes are derived based on the fiber length and the computed or derive critical length of fiber. Longitudinal and Transverse module of Polymer Matrix Composite consisting of seven layers with different fiber volume fractions and different fibers orientations at 0,15,30,45,60,75 and 90 degrees are analyzed through Rule-of Mixture material design model. The analysis results are represented in different graphical steps and have been measured with statistical parameters. This data mining application implemented here has focused the mechanical problems of material design and analysis. Therefore, this system is an expert decision support system for optimizing the materials performance for designing light-weight and strong, and cost effective polymer composite materials.
Reliable Robust and Real-Time Communication Protocol for Data Delivery in Wireless sensor Networks
Venue: arXiv cs.NI 2013
Year: 2013

WSNs can be considered a distributed control system designed to react to sensor information with an effective and timely action. For this reason, in WSNs it is important to provide real-time coordination and communication to guarantee timely execution of the right actions. In this paper a new communication protocol RRRT to support robust real-time and reliable event data delivery with minimum energy consumption and with congestion avoidance in WSNs is proposed. The proposed protocol uses the fault tolerant optimal path for data delivery. The proposed solution dynamically adjust their protocol configurations to adapt to the heterogeneous characteristics of WSNs. Specifically, the interactions between contention resolution and congestion control mechanisms as well as the physical layer effects in WSNs are investigated.
Worst-case Asymmetric Distributed Source Coding
Venue: arXiv cs.IT 2013
Year: 2013

We consider a worst-case asymmetric distributed source coding problem where an information sink communicates with $N$ correlated information sources to gather their data. A data-vector $\bar{x} = (x_1, ..., x_N) \sim {\mathcal P}$ is derived from a discrete and finite joint probability distribution ${\mathcal P} = p(x_1, ..., x_N)$ and component $x_i$ is revealed to the $i^{\textrm{th}}$ source, $1 \le i \le N$. We consider an asymmetric communication scenario where only the sink is assumed to know distribution $\mathcal P$. We are interested in computing the minimum number of bits that the sources must send, in the worst-case, to enable the sink to losslessly learn any $\bar{x}$ revealed to the sources. We propose a novel information measure called information ambiguity to perform the worst-case information-theoretic analysis and prove its various properties. Then, we provide interactive communication protocols to solve the above problem in two different communication scenarios. We also investigate the role of block-coding in the worst-case analysis of distributed compression problem and prove that it offers almost no compression advantage compared to the scenarios where this problem is addressed, as in this paper, with only a single instance of data-vector.
Evaluation of a Multi-Resolution Dyadic Wavelet Transform Method for usable Speech Detection
Venue: arXiv cs.SD 2013
Year: 2013

Many applications of speech communication and speaker identification suffer from the problem of co-channel speech. This paper deals with a multi-resolution dyadic wavelet transform method for usable segments of co-channel speech detection that could be processed by a speaker identification system. Evaluation of this method is performed on TIMIT database referring to the Target to Interferer Ratio measure. Co-channel speech is constructed by mixing all possible gender speakers. Results do not show much difference for different mixtures. For the overall mixtures 95.76% of usable speech is correctly detected with false alarms of 29.65%.
Wyner-Ziv Coding in the Real Field Based on BCH-DFT Codes
Venue: arXiv cs.IT 2013
Year: 2013

We show how real-number codes can be used to compress correlated sources and establish a new framework for distributed lossy source coding, in which we quantize compressed sources instead of compressing quantized sources. This change in the order of binning and quantization blocks makes it possible to model correlation between continuous-valued sources more realistically and compensate for the quantization error when the sources are completely correlated. We focus on the asymmetric case, i.e., lossy source coding with side information at the decoder, also known as Wyner-Ziv coding. The encoding and decoding procedures are described in detail for discrete Fourier transform (DFT) codes, both for syndrome- and parity-based approaches. We also extend the parity-based approach to the case where the transmission channel is noisy and perform distributed joint source-channel coding in this context. The proposed system is well suited for low-delay communications. Furthermore, the mean-squared reconstruction error (MSE) is shown to be less than or close to the quantization error level, the ideal case in coding based on binary codes.
The Piggy Bank Cryptographic Trope
Venue: arXiv cs.CR 2013
Year: 2013

This paper presents applications of the trope of the locked and sealed piggy-bank into which the secret can be easily inserted but from which it cannot be withdrawn without opening the box. We present a basic two-pass cryptographic scheme that can serve as template for a variety of implementations. Together with the sealed piggy-bank is sent a coded letter that lists and certifies the contents of the box. We show how this idea can help increase the security of cryptographic protocols for classical systems as well as those based on "single-state" systems. More specifically, we propose the use of a hashing digest (instead of the coded letter) to detect loss of key bits to the eavesdropper and use in communication systems where error correction is an important issue.
The Parameterized Complexity of some Permutation Group Problems
Venue: arXiv cs.CC 2013
Year: 2013

In this paper we study the parameterized complexity of two well-known permutation group problems which are NP-complete. 1. Given a permutation group G=<S>, subgroup of $S_n$, and a parameter $k$, find a permutation $π$ in G such that $|{i\in [n]\mid π(i)\ne i}|$ is at least $k$. This generalizes the well-known NP-complete problem of finding a fixed-point free permutation in G. (this is the case when $k=n$). We show that this problem with parameter $k$ is fixed parameter tractable. In the process, we give a simple deterministic polynomial-time algorithm for finding a fixed point free element in a transitive permutation group, answering an open question of Cameron. 2. Next we consider the problem of computing a base for a permutation group G=<S>. A base for G is a subset B of $[n]$ such that the subgroup of G that fixes B pointwise is trivial. This problem is known to be NP-complete. We show that it is fixed parameter tractable for the case of cyclic permutation groups and for permutation groups of constant orbit size. For more general classes of permutation groups we do not know whether the problem is in FPT or is W[1]-hard.
Matroid and Knapsack Center Problems
Venue: arXiv cs.DS 2013
Year: 2013

In the classic $k$-center problem, we are given a metric graph, and the objective is to open $k$ nodes as centers such that the maximum distance from any vertex to its closest center is minimized. In this paper, we consider two important generalizations of $k$-center, the matroid center problem and the knapsack center problem. Both problems are motivated by recent content distribution network applications. Our contributions can be summarized as follows: 1. We consider the matroid center problem in which the centers are required to form an independent set of a given matroid. We show this problem is NP-hard even on a line. We present a 3-approximation algorithm for the problem on general metrics. We also consider the outlier version of the problem where a given number of vertices can be excluded as the outliers from the solution. We present a 7-approximation for the outlier version. 2. We consider the (multi-)knapsack center problem in which the centers are required to satisfy one (or more) knapsack constraint(s). It is known that the knapsack center problem with a single knapsack constraint admits a 3-approximation. However, when there are at least two knapsack constraints, we show this problem is not approximable at all. To complement the hardness result, we present a polynomial time algorithm that gives a 3-approximate solution such that one knapsack constraint is satisfied and the others may be violated by at most a factor of $1+ε$. We also obtain a 3-approximation for the outlier version that may violate the knapsack constraint by $1+ε$.
libcppa - Designing an Actor Semantic for C++11
Venue: arXiv cs.PL 2013
Year: 2013

Parallel hardware makes concurrency mandatory for efficient program execution. However, writing concurrent software is both challenging and error-prone. C++11 provides standard facilities for multiprogramming, such as atomic operations with acquire/release semantics and RAII mutex locking, but these primitives remain too low-level. Using them both correctly and efficiently still requires expert knowledge and hand-crafting. The actor model replaces implicit communication by sharing with an explicit message passing mechanism. It applies to concurrency as well as distribution, and a lightweight actor model implementation that schedules all actors in a properly pre-dimensioned thread pool can outperform equivalent thread-based applications. However, the actor model did not enter the domain of native programming languages yet besides vendor-specific island solutions. With the open source library libcppa, we want to combine the ability to build reliable and distributed systems provided by the actor model with the performance and resource-efficiency of C++11.
On Event Triggered Tracking for Nonlinear Systems
Venue: arXiv cs.SY 2013
Year: 2013

In this paper we study an event based control algorithm for trajectory tracking in nonlinear systems. The desired trajectory is modelled as the solution of a reference system with an exogenous input and it is assumed that the desired trajectory and the exogenous input to the reference system are uniformly bounded. Given a continuous-time control law that guarantees global uniform asymptotic tracking of the desired trajectory, our algorithm provides an event based controller that not only guarantees uniform ultimate boundedness of the tracking error, but also ensures non-accumulation of inter-execution times. In the case that the derivative of the exogenous input to the reference system is also uniformly bounded, an arbitrarily small ultimate bound can be designed. If the exogenous input to the reference system is piecewise continuous and not differentiable everywhere then the achievable ultimate bound is constrained and the result is local, though with a known region of attraction. The main ideas in the paper are illustrated through simulations of trajectory tracking by a nonlinear system.
Cellular Systems with Many Antennas: Large System Analysis under Pilot Contamination
Venue: arXiv cs.IT 2013
Year: 2013

Base stations with a large number of transmit antennas have the potential to serve a large number of users simultaneously at higher rates. They also promise a lower power consumption due to coherent combining at the receiver. However, the receiver processing in the uplink relies on the channel estimates which are known to suffer from pilot interference. In this work, we perform an uplink large system analysis of multi-cell multi-antenna system when the receiver employs a matched filtering with a pilot contaminated estimate. We find the asymptotic Signal to Interference plus Noise Ratio (SINR) as the number of antennas and number of users per base station grow large while maintaining a fixed ratio. To do this, we make use of the similarity of the uplink received signal in a multi-antenna system to the representation of the received signal in CDMA systems. The asymptotic SINR expression explicitly captures the effect of pilot contamination and that of interference averaging. This also explains the SINR performance of receiver processing schemes at different regimes such as instances when the number of antennas are comparable to number of users as well as when antennas exceed greatly the number of users. Finally, we also propose that the adaptive MMSE symbol detection scheme, which does not require the explicit channel knowledge, can be employed for cellular systems with large number of antennas.