OpenRaiser/Intern-Atlas huggingface dataset:
Scilab and SIP for Image Processing
Venue: arXiv cs.MS 2012
Year: 2012

This paper is an overview of Image Processing and Analysis using Scilab, a free prototyping environment for numerical calculations similar to Matlab. We demonstrate the capabilities of SIP -- the Scilab Image Processing Toolbox -- which extends Scilab with many functions to read and write images in over 100 major file formats, including PNG, JPEG, BMP, and TIFF. It also provides routines for image filtering, edge detection, blurring, segmentation, shape analysis, and image recognition. Basic directions to install Scilab and SIP are given, and also a mini-tutorial on Scilab. Three practical examples of image analysis are presented, in increasing degrees of complexity, showing how advanced image analysis techniques seems uncomplicated in this environment.
New decoding scheme for LDPC codes based on simple product code structure
Venue: arXiv cs.IT 2012
Year: 2012

In this paper, a new decoding scheme for low-density parity-check (LDPC) codes using the concept of simple product code structure is proposed based on combining two independently received soft-decision data for the same codeword. LDPC codes act as horizontal codes of the product codes and simple algebraic codes are used as vertical codes to help decoding of the LDPC codes. The decoding capability of the proposed decoding scheme is defined and analyzed using the paritycheck matrices of vertical codes and especially the combined-decodability is derived for the case of single parity-check (SPC) and Hamming codes being used as vertical codes. It is also shown that the proposed decoding scheme achieves much better error-correcting capability in high signal to noise ratio (SNR) region with low additional decoding complexity, compared with a conventional decoding scheme.
When the Cut Condition is Enough: A Complete Characterization for Multiflow Problems in Series-Parallel Networks
Venue: arXiv cs.DM 2012
Year: 2012

Let $G=(V,E)$ be a supply graph and $H=(V,F)$ a demand graph defined on the same set of vertices. An assignment of capacities to the edges of $G$ and demands to the edges of $H$ is said to satisfy the \emph{cut condition} if for any cut in the graph, the total demand crossing the cut is no more than the total capacity crossing it. The pair $(G,H)$ is called \emph{cut-sufficient} if for any assignment of capacities and demands that satisfy the cut condition, there is a multiflow routing the demands defined on $H$ within the network with capacities defined on $G$. We prove a previous conjecture, which states that when the supply graph $G$ is series-parallel, the pair $(G,H)$ is cut-sufficient if and only if $(G,H)$ does not contain an \emph{odd spindle} as a minor; that is, if it is impossible to contract edges of $G$ and delete edges of $G$ and $H$ so that $G$ becomes the complete bipartite graph $K_{2,p}$, with $p\geq 3$ odd, and $H$ is composed of a cycle connecting the $p$ vertices of degree 2, and an edge connecting the two vertices of degree $p$. We further prove that if the instance is \emph{Eulerian} --- that is, the demands and capacities are integers and the total of demands and capacities incident to each vertex is even --- then the multiflow problem has an integral solution. We provide a polynomial-time algorithm to find an integral solution in this case. In order to prove these results, we formulate properties of tight cuts (cuts for which the cut condition inequality is tight) in cut-sufficient pairs. We believe these properties might be useful in extending our results to planar graphs.
Quartile Clustering: A quartile based technique for Generating Meaningful Clusters
Venue: arXiv cs.DB 2012
Year: 2012

Clustering is one of the main tasks in exploratory data analysis and descriptive statistics where the main objective is partitioning observations in groups. Clustering has a broad range of application in varied domains like climate, business, information retrieval, biology, psychology, to name a few. A variety of methods and algorithms have been developed for clustering tasks in the last few decades. We observe that most of these algorithms define a cluster in terms of value of the attributes, density, distance etc. However these definitions fail to attach a clear meaning/semantics to the generated clusters. We argue that clusters having understandable and distinct semantics defined in terms of quartiles/halves are more appealing to business analysts than the clusters defined by data boundaries or prototypes. On the samepremise, we propose our new algorithm named as quartile clustering technique. Through a series of experiments we establish efficacy of this algorithm. We demonstrate that the quartile clustering technique adds clear meaning to each of the clusters compared to K-means. We use DB Index to measure goodness of the clusters and show our method is comparable to EM (Expectation Maximization), PAM (Partition around Medoid) and K Means. We have explored its capability in detecting outlier and the benefit of added semantics. We discuss some of the limitations in its present form and also provide a rough direction in addressing the issue of merging the generated clusters.
Linear MMSE-Optimal Turbo Equalization Using Context Trees
Venue: arXiv cs.SY 2012
Year: 2012

Formulations of the turbo equalization approach to iterative equalization and decoding vary greatly when channel knowledge is either partially or completely unknown. Maximum aposteriori probability (MAP) and minimum mean square error (MMSE) approaches leverage channel knowledge to make explicit use of soft information (priors over the transmitted data bits) in a manner that is distinctly nonlinear, appearing either in a trellis formulation (MAP) or inside an inverted matrix (MMSE). To date, nearly all adaptive turbo equalization methods either estimate the channel or use a direct adaptation equalizer in which estimates of the transmitted data are formed from an expressly linear function of the received data and soft information, with this latter formulation being most common. We study a class of direct adaptation turbo equalizers that are both adaptive and nonlinear functions of the soft information from the decoder. We introduce piecewise linear models based on context trees that can adaptively approximate the nonlinear dependence of the equalizer on the soft information such that it can choose both the partition regions as well as the locally linear equalizer coefficients in each region independently, with computational complexity that remains of the order of a traditional direct adaptive linear equalizer. This approach is guaranteed to asymptotically achieve the performance of the best piecewise linear equalizer and we quantify the MSE performance of the resulting algorithm and the convergence of its MSE to that of the linear minimum MSE estimator as the depth of the context tree and the data length increase.
Research collaboration and the expanding science grid: Measuring globalization processes worldwide
Venue: arXiv cs.DL 2012
Year: 2012

This paper applies a new model and analytical tool to measure and study contemporary globalization processes in collaborative science - a world in which scientists, scholars, technicians and engineers interact within a 'grid' of interconnected research sites and collaboration networks. The building blocks of our metrics are the cities where scientific research is conducted, as mentioned in author addresses on research publications. The unit of analysis is the geographical distance between those cities. In our macro-level trend analysis, covering the years 2000-2010, we observe that research collaboration distances have been increasing, while the share of collaborative contacts with foreign cities has leveled off. Collaboration distances and growth rates differ significantly between countries and between fields of science. The application of a distance metrics to compare and track these processes opens avenues for further studies, both at the meso-level and at the micro-level, into how research collaboration patterns and trends are driving and shaping the connectivity fabric of world science.
A New Analysis of an Adaptive Convex Mixture: A Deterministic Approach
Venue: arXiv cs.SY 2012
Year: 2012

We introduce a new analysis of an adaptive mixture method that combines outputs of two constituent filters running in parallel to model an unknown desired signal. This adaptive mixture is shown to achieve the mean square error (MSE) performance of the best constituent filter, and in some cases outperforms both, in the steady-state. However, the MSE analysis of this mixture in the steady-state and during the transient regions uses approximations and relies on statistical models on the underlying signals and systems. Hence, such an analysis may not be useful or valid for signals generated by various real life systems that show high degrees of nonstationarity, limit cycles and, in many cases, that are even chaotic. To this end, we perform the transient and the steady-state analysis of this adaptive mixture in a "strong" deterministic sense without any approximations in the derivations or statistical assumptions on the underlying signals such that our results are guaranteed to hold. In particular, we relate the time-accumulated squared estimation error of this adaptive mixture at any time to the time-accumulated squared estimation error of the optimal convex mixture of the constituent filters directly tuned to the underlying signal in an individual sequence manner.
Do Linguistic Style and Readability of Scientific Abstracts affect their Virality?
Venue: arXiv cs.SI 2012
Year: 2012

Reactions to textual content posted in an online social network show different dynamics depending on the linguistic style and readability of the submitted content. Do similar dynamics exist for responses to scientific articles? Our intuition, supported by previous research, suggests that the success of a scientific article depends on its content, rather than on its linguistic style. In this article, we examine a corpus of scientific abstracts and three forms of associated reactions: article downloads, citations, and bookmarks. Through a class-based psycholinguistic analysis and readability indices tests, we show that certain stylistic and readability features of abstracts clearly concur in determining the success and viral capability of a scientific article.
On optimum parameter modulation-estimation from a large deviations perspective
Venue: arXiv cs.IT 2012
Year: 2012

We consider the problem of jointly optimum modulation and estimation of a real-valued random parameter, conveyed over an additive white Gaussian noise (AWGN) channel, where the performance metric is the large deviations behavior of the estimator, namely, the exponential decay rate (as a function of the observation time) of the probability that the estimation error would exceed a certain threshold. Our basic result is in providing an exact characterization of the fastest achievable exponential decay rate, among all possible modulator-estimator (transmitter-receiver) pairs, where the modulator is limited only in the signal power, but not in bandwidth. This exponential rate turns out to be given by the reliability function of the AWGN channel. We also discuss several ways to achieve this optimum performance, and one of them is based on quantization of the parameter, followed by optimum channel coding and modulation, which gives rise to a separation-based transmitter, if one views this setting from the perspective of joint source-channel coding. This is in spite of the fact that, in general, when error exponents are considered, the source-channel separation theorem does not hold true. We also discuss several observations, modifications and extensions of this result in several directions, including other channels, and the case of multidimensional parameter vectors. One of our findings concerning the latter, is that there is an abrupt threshold effect in the dimensionality of the parameter vector: below a certain critical dimension, the probability of excess estimation error may still decay exponentially, but beyond this value, it must converge to unity.
Can an Ad-hoc ontology Beat a Medical Search Engine? The Chronious Search Engine case
Venue: arXiv cs.IR 2012
Year: 2012

Chronious is an Open, Ubiquitous and Adaptive Chronic Disease Management Platform for Chronic Obstructive Pulmonary Disease(COPD) Chronic Kidney Disease (CKD) and Renal Insufficiency. It consists of several modules: an ontology based literature search engine, a rule based decision support system, remote sensors interacting with lifestyle interfaces (PDA, monitor touch-screen) and a machine learning module. All these modules interact each other to allow the monitoring of two types of chronic diseases and to help clinician in taking decision for care purpose. This paper illustrates how the ontology search engine was created and fed and how some comparative test indicated that the ontology based approach give better results, on some estimation parameters, than the main reference web search engine.
Multi-Antenna System Design with Bright Transmitters and Blind Receivers
Venue: arXiv cs.IT 2012
Year: 2012

This paper considers a scenario for multi-input multi-output (MIMO) communication systems when perfect channel state information at the transmitter (CSIT) is given while the equivalent channel state information at the receiver (CSIR) is not available. Such an assumption is valid for the downlink multi-user MIMO systems with linear precoders that depend on channels to all receivers. We propose a concept called dual systems with zero-forcing designs based on the duality principle, originally proposed to relate Gaussian multi-access channels (MACs) and Gaussian broadcast channels (BCs). For the two-user N*2 MIMO BC with N antennas at the transmitter and two antennas at each of the receivers, we design a downlink interference cancellation (IC) transmission scheme using the dual of uplink MAC systems employing IC methods. The transmitter simultaneously sends two precoded Alamouti codes, one for each user. Each receiver can zero-force the unintended user's Alamouti codes and decouple its own data streams using two simple linear operations independent of CSIR. Analysis shows that the proposed scheme achieves a diversity gain of 2(N-1) for equal energy constellations with short-term power and rate constraints. Power allocation between two users can also be performed, and it improves the array gain but not the diversity gain. Numerical results demonstrate that the bit error rate of the downlink IC scheme has a substantial gain compared to the block diagonalization method, which requires global channel information at each node.
A Novel Approach for Secure Data Aggregation in Wireless Sensor Networks
Venue: arXiv cs.CR 2012
Year: 2012

The Wireless Sensor Networks (WSNs) are composed of resource starved sensor nodes that are deployed to sense, process and communicate vital information to the base station. Due to the stringent constraints on the resources in the sensor nodes on one hand and due to the communications costs being always significantly higher than the data processing costs, the WSNs typically, employ in-network processing, which aims at reducing effectively, the total number of packets eventually transmitted to the base station. Such innetwork processing largely employs data aggregation operations that aggregate the data into a compact representation for further transmission. However, due to the ubiquitous & pervasive deployment, heavier resource demands of the security protocols and due to the stringent resource constraints in WSN nodes, the security concerns in WSNs are even otherwise critical. These concerns assume alarming proportions when using data aggregation in which the output of the data aggregator nodes depends on that of various other nodes. Hence, the protocols for data aggregation have to carefully devised with a constant vigil on ensuring security of the data. In this paper, based on our survey of the existing research efforts for ensuring secure data aggregation, we propose a novel approach using homomorphic encryption and additive digital signatures to achieve confidentiality, integrity and availability for secure data aggregation in wireless sensor networks.
On Irrelevance and Algorithmic Equality in Predicative Type Theory
Venue: arXiv cs.LO 2012
Year: 2012

Dependently typed programs contain an excessive amount of static terms which are necessary to please the type checker but irrelevant for computation. To separate static and dynamic code, several static analyses and type systems have been put forward. We consider Pfenning's type theory with irrelevant quantification which is compatible with a type-based notion of equality that respects eta-laws. We extend Pfenning's theory to universes and large eliminations and develop its meta-theory. Subject reduction, normalization and consistency are obtained by a Kripke model over the typed equality judgement. Finally, a type-directed equality algorithm is described whose completeness is proven by a second Kripke model.
UML modelling of geographic routing protocol "Greedy Perimeter Stateless Routing" for its integration into the "Java Network Simulator"
Venue: arXiv cs.NI 2012
Year: 2012

In this work we propose an UML modeling of the "Greedy Perimeter Stateless Routing" (GPSR) protocol that integrate this geographic routing protocol, into "JavaNetwork Simulator" to simulate and study this protocol in a first time and offer some improvement in these features. Java Network Simulator (JNS) is a project of "translation" of Network Simulator (NS) in Java initiated by "the UCL Department of Computer Science". This simulator is not as complete as ns-2, but it is much more accessible to programmers unfamiliar with Tcl. Java Network Simulator does not support so far, no routing protocol for vehicular ad hoc networks and all the routing decisions are made statically or using RIP and OSPF. By modeling and integrating the routing protocol GPSR to JNS, users will be able to understand the concept of the geographic routing and how the routing information is transmitted and updated between nodes in vehicular ad hoc network. The article first examines the architecture of the Java Network Simulator, then gives a brief review of the routing protocol GPSR and finally presents our UML modeling incorporating GPSR in the Java Network Simulator.
Texture Classification Approach Based on Combination of Edge & Co-occurrence and Local Binary Pattern
Venue: arXiv cs.CV 2012
Year: 2012

Texture classification is one of the problems which has been paid much attention on by computer scientists since late 90s. If texture classification is done correctly and accurately, it can be used in many cases such as Pattern recognition, object tracking, and shape recognition. So far, there have been so many methods offered to solve this problem. Near all these methods have tried to extract and define features to separate different labels of textures really well. This article has offered an approach which has an overall process on the images of textures based on Local binary pattern and Gray Level Co-occurrence matrix and then by edge detection, and finally, extracting the statistical features from the images would classify them. Although, this approach is a general one and is could be used in different applications, the method has been tested on the stone texture and the results have been compared with some of the previous approaches to prove the quality of proposed approach.
Large-System Analysis of Joint User Selection and Vector Precoding with Zero-Forcing Transmit Beamforming for MIMO Broadcast Channels
Venue: arXiv cs.IT 2012
Year: 2012

Multiple-input multiple-output (MIMO) broadcast channels (BCs) (MIMO-BCs) with perfect channel state information (CSI) at the transmitter are considered. As joint user selection (US) and vector precoding (VP) (US-VP) with zero-forcing transmit beamforming (ZF-BF), US and continuous VP (CVP) (US-CVP) and data-dependent US (DD-US) are investigated. The replica method, developed in statistical physics, is used to analyze the energy penalties for the two US-VP schemes in the large-system limit, where the number of users, the number of selected users, and the number of transmit antennas tend to infinity with their ratios kept constant. Four observations are obtained in the large-system limit: First, the assumptions of replica symmetry (RS) and 1-step replica symmetry breaking (1RSB) for DD-US can provide acceptable approximations for low and moderate system loads, respectively. Secondly, DD-US outperforms CVP with random US in terms of the energy penalty for low-to-moderate system loads. Thirdly, the asymptotic energy penalty of DD-US is indistinguishable from that of US-CVP for low system loads. Finally, a greedy algorithm of DD-US proposed in authors' previous work can achieve nearly optimal performance for low-to-moderate system loads.
A Flexible Channel Coding Approach for Short-Length Codewords
Venue: arXiv cs.IT 2012
Year: 2012

This letter introduces a novel channel coding design framework for short-length codewords that permits balancing the tradeoff between the bit error rate floor and waterfall region by modifying a single real-valued parameter. The proposed approach is based on combining convolutional coding with a $q$-ary linear combination and unequal energy allocation, the latter being controlled by the aforementioned parameter. EXIT charts are used to shed light on the convergence characteristics of the associated iterative decoder, which is described in terms of factor graphs. Simulation results show that the proposed scheme is able to adjust its end-to-end error rate performance efficiently and easily, on the contrary to previous approaches that require a full code redesign when the error rate requirements of the application change. Simulations also show that, at mid-range bit-error rates, there is a small performance penalty with respect to the previous approaches. However, the EXIT chart analysis and the simulation results suggest that for very low bit-error rates the proposed system will exhibit lower error floors than previous approaches.
Hybridizing PSM and RSM Operator for Solving NP-Complete Problems: Application to Travelling Salesman Problem
Venue: arXiv cs.NE 2012
Year: 2012

In this paper, we present a new mutation operator, Hybrid Mutation (HPRM), for a genetic algorithm that generates high quality solutions to the Traveling Salesman Problem (TSP). The Hybrid Mutation operator constructs an offspring from a pair of parents by hybridizing two mutation operators, PSM and RSM. The efficiency of the HPRM is compared as against some existing mutation operators; namely, Reverse Sequence Mutation (RSM) and Partial Shuffle Mutation (PSM) for BERLIN52 as instance of TSPLIB. Experimental results show that the new mutation operator is better than the RSM and PSM.