OpenRaiser/Intern-Atlas huggingface dataset:
Biased Assimilation, Homophily and the Dynamics of Polarization
Venue: arXiv cs.SI 2012
Year: 2012

Are we as a society getting more polarized, and if so, why? We try to answer this question through a model of opinion formation. Empirical studies have shown that homophily results in polarization. However, we show that DeGroot's well-known model of opinion formation based on repeated averaging can never be polarizing, even if individuals are arbitrarily homophilous. We generalize DeGroot's model to account for a phenomenon well-known in social psychology as biased assimilation: when presented with mixed or inconclusive evidence on a complex issue, individuals draw undue support for their initial position thereby arriving at a more extreme opinion. We show that in a simple model of homophilous networks, our biased opinion formation process results in either polarization, persistent disagreement or consensus depending on how biased individuals are. In other words, homophily alone, without biased assimilation, is not sufficient to polarize society. Quite interestingly, biased assimilation also provides insight into the following related question: do internet based recommender algorithms that show us personalized content contribute to polarization? We make a connection between biased assimilation and the polarizing effects of some random-walk based recommender algorithms that are similar in spirit to some commonly used recommender algorithms.
Receiver Design for Realizing On-Demand WiFi Wake-up using WLAN Signals
Venue: arXiv cs.NI 2012
Year: 2012

In this paper, we design a simple, low-cost, and low-power wake-up receiver which can be used for an IEEE 802.11-compliant device to remotely wake up the other devices by utilizing its own wireless LAN (WLAN) signals. The employed wake-up mechanism utilizes the length of 802.11 data frame generated by a WiFi transmitter to differentiate the information conveyed to the wake-up receiver. The wake-up receiver is designed to reliably detect the length of transmitted data frame only with simple envelope detection and limited signal processing. We develop a prototype of the wake-up receiver and investigate the detection performance of the envelope of 802.11 signals. Our numerical results show that the proposed wake-up receiver achieves much larger detection range than the off-the-shelf, commercial receiver having the similar functionality.
Highly Available Smart Grid Control Centers through Intrusion Tolerance
Venue: arXiv cs.CR 2012
Year: 2012

Societies' norms of operation relies on the proper and secure functioning of several critical infrastructures, particularly modern power grid which is also known as smart grid. Smart grid is interwoven with the information and communication technology infrastructure, and thus it is exposed to cyber security threats. Intrusion tolerance proves a promising security approach against malicious attacks and contributes to enhance the resilience and security of the key components of smart grid, mainly SCADA and control centers. Hence, an intrusion tolerant system architecture for smart grid control centers is proposed in this paper. The proposed architecture consists of several modules namely, replication & diversity, compromised/faulty replica detector, reconfiuration, auditing and proxy. Some of distinctive features of the proposed ITS are diversity as well as the combined and fine-grained rejuvenation approach. The security of the proposed architecture is evaluated with regard to availability and mean time to security failure as performance measures. The analysis is conducted using a Discrete Time Semi Markov Model and the acquired results show improvements compared to two established intrusion tolerant architectures. The viability of SLA as another performance metric is also investigated.
The Hidden Internet of Iran: Private Address Allocations on a National Network
Venue: arXiv cs.NI 2012
Year: 2012

While funding agencies have provided substantial support for the developers and vendors of services that facilitate the unfettered flow of information through the Internet, little consolidated knowledge exists on the basic communications network infrastructure of the Islamic Republic of Iran. In the absence open access and public data, rumors and fear have reigned supreme. During provisional research on the country's censorship regime, we found initial indicators that telecommunications entities in Iran allowed private addresses to route domestically, whether intentionally or unintentionally, creating a hidden network only reachable within the country. Moreover, records such as DNS entries lend evidence of a 'dual stack' approach, wherein servers are assigned a domestic IP addresses, in addition to a global one. Despite the clear political implications of the claim we put forward, particularly in light of rampant speculation regarding the mandate of Article 46 of the 'Fifth Five Year Development Plan' to establish a "national information network," we refrain from hypothesizing the purpose of this structure. In order to solicit critical feedback for future research, we outline our initial findings and attempt to demonstrate that the matter under contention is a nation-wide phenomenom that warrants broader attention.
Spatial Indexing of Large Multidimensional Databases
Venue: arXiv cs.DB 2012
Year: 2012

Scientific endeavors such as large astronomical surveys generate databases on the terabyte scale. These, usually multidimensional databases must be visualized and mined in order to find interesting objects or to extract meaningful and qualitatively new relationships. Many statistical algorithms required for these tasks run reasonably fast when operating on small sets of in-memory data, but take noticeable performance hits when operating on large databases that do not fit into memory. We utilize new software technologies to develop and evaluate fast multidimensional indexing schemes that inherently follow the underlying, highly non-uniform distribution of the data: they are layered uniform grid indices, hierarchical binary space partitioning, and sampled flat Voronoi tessellation of the data. Our working database is the 5-dimensional magnitude space of the Sloan Digital Sky Survey with more than 270 million data points, where we show that these techniques can dramatically speed up data mining operations such as finding similar objects by example, classifying objects or comparing extensive simulation sets with observations. We are also developing tools to interact with the multidimensional database and visualize the data at multiple resolutions in an adaptive manner.
Data compression of dynamic set-valued information systems
Venue: arXiv cs.IT 2012
Year: 2012

This paper further investigates the set-valued information system. First, we bring forward three tolerance relations for set-valued information systems and explore their basic properties in detail. Then the data compression is investigated for attribute reductions of set-valued information systems. Afterwards, we discuss the data compression of dynamic set-valued information systems by utilizing the precious compression of the original systems. Several illustrative examples are employed to show that attribute reductions of set-valued information systems can be simplified significantly by our proposed approach.
Sparse Modeling of Intrinsic Correspondences
Venue: arXiv cs.GR 2012
Year: 2012

We present a novel sparse modeling approach to non-rigid shape matching using only the ability to detect repeatable regions. As the input to our algorithm, we are given only two sets of regions in two shapes; no descriptors are provided so the correspondence between the regions is not know, nor we know how many regions correspond in the two shapes. We show that even with such scarce information, it is possible to establish very accurate correspondence between the shapes by using methods from the field of sparse modeling, being this, the first non-trivial use of sparse models in shape correspondence. We formulate the problem of permuted sparse coding, in which we solve simultaneously for an unknown permutation ordering the regions on two shapes and for an unknown correspondence in functional representation. We also propose a robust variant capable of handling incomplete matches. Numerically, the problem is solved efficiently by alternating the solution of a linear assignment and a sparse coding problem. The proposed methods are evaluated qualitatively and quantitatively on standard benchmarks containing both synthetic and scanned objects.
Optimistic Agents are Asymptotically Optimal
Venue: arXiv cs.AI 2012
Year: 2012

We use optimism to introduce generic asymptotically optimal reinforcement learning agents. They achieve, with an arbitrary finite or compact class of environments, asymptotically optimal behavior. Furthermore, in the finite deterministic case we provide finite error bounds.
On the Sum of Squared η-μRandom Variates With Application to the Performance of Wireless Communication Systems
Venue: arXiv cs.IT 2012
Year: 2012

The probability density function (PDF) and cumulative distribution function of the sum of L independent but not necessarily identically distributed squared η-μvariates, applicable to the output statistics of maximal ratio combining (MRC) receiver operating over η-μfading channels that includes the Hoyt and the Nakagami-m models as special cases, is presented in closed-form in terms of the Fox's H-bar function. Further analysis, particularly on the bit error rate via PDF-based approach, is also represented in closed form in terms of the extended Fox's H-bar function (H-hat). The proposed new analytical results complement previous results and are illustrated by extensive numerical and Monte Carlo simulation results.
Implementation of Privacy-preserving SimRank over Distributed Information Network
Venue: arXiv cs.CR 2012
Year: 2012

Information network analysis has drawn a lot attention in recent years. Among all the aspects of network analysis, similarity measure of nodes has been shown useful in many applications, such as clustering, link prediction and community identification, to name a few. As linkage data in a large network is inherently sparse, it is noted that collecting more data can improve the quality of similarity measure. This gives different parties a motivation to cooperate. In this paper, we address the problem of link-based similarity measure of nodes in an information network distributed over different parties. Concerning the data privacy, we propose a privacy-preserving SimRank protocol based on fully-homomorphic encryption to provide cryptographic protection for the links.
External Memory based Distributed Generation of Massive Scale Social Networks on Small Clusters
Venue: arXiv cs.DB 2012
Year: 2012

Small distributed systems are limited by their main memory to generate massively large graphs. Trivial extension to current graph generators to utilize external memory leads to large amount of random I/O hence do not scale with size. In this work we offer a technique to generate massive scale graphs on small cluster of compute nodes with limited main memory. We develop several distributed and external memory algorithms, primarily, shuffle, relabel, redistribute, and, compressed-sparse-row (csr) convert. The algorithms are implemented in MPI/pthread model to help parallelize the operations across multicores within each core. Using our scheme it is feasible to generate a graph of size $2^{38}$ nodes (scale 38) using only 64 compute nodes. This can be compared with the current scheme would require at least 8192 compute node, assuming 64GB of main memory. Our work has broader implications for external memory graph libraries such as STXXL and graph processing on SSD-based supercomputers such as Dash and Gordon [1][2].
A New Generalized Closed Form Expression for Average Bit Error Probability Over Rayleigh Fading Channel
Venue: arXiv cs.IT 2012
Year: 2012

Except for a few simple digital modulation techniques, derivation of average bit error probability over fading channels is difficult and is an involved process. In this letter, curve fitting technique has been employed to express bit error probability over AWGN of any digital modulation scheme in terms of a simple Gaussian function. Using this Gaussian function, a generalized closed form expression for computing average probability of bit error over Rayleigh fading channels has been derived. Excellent agreement has been found between error probabilities computed with our method and the rigorously calculated error probabilities of several digital modulation schemes.
Two Species Evolutionary Game Model of User and Moderator Dynamics
Venue: arXiv cs.GT 2012
Year: 2012

We construct a two species evolutionary game model of an online society consisting of ordinary users and behavior enforcers (moderators). Among themselves, moderators play a coordination game choosing between being "positive" or "negative" (or harsh) while ordinary users play prisoner's dilemma. When interacting, moderators motivate good behavior (cooperation) among the users through punitive actions while the moderators themselves are encouraged or discouraged in their strategic choice by these interactions. We show the following results: (i) We show that the $ω$-limit set of the proposed system is sensitive both to the degree of punishment and the proportion of moderators in closed form. (ii) We demonstrate that the basin of attraction for the Pareto optimal strategy $(\text{Cooperate},\text{Positive})$ can be computed exactly. (iii) We demonstrate that for certain initial conditions the system is self-regulating. These results partially explain the stability of many online users communities such as Reddit. We illustrate our results with examples from this online system.
Intra-Retinal Layer Segmentation of 3D Optical Coherence Tomography Using Coarse Grained Diffusion Map
Venue: arXiv cs.CV 2012
Year: 2012

Optical coherence tomography (OCT) is a powerful and noninvasive method for retinal imaging. In this paper, we introduce a fast segmentation method based on a new variant of spectral graph theory named diffusion maps. The research is performed on spectral domain (SD) OCT images depicting macular and optic nerve head appearance. The presented approach does not require edge-based image information and relies on regional image texture. Consequently, the proposed method demonstrates robustness in situations of low image contrast or poor layer-to-layer image gradients. Diffusion mapping is applied to 2D and 3D OCT datasets composed of two steps, one for partitioning the data into important and less important sections, and another one for localization of internal layers.In the first step, the pixels/voxels are grouped in rectangular/cubic sets to form a graph node.The weights of a graph are calculated based on geometric distances between pixels/voxels and differences of their mean intensity.The first diffusion map clusters the data into three parts, the second of which is the area of interest. The other two sections are eliminated from the remaining calculations. In the second step, the remaining area is subjected to another diffusion map assessment and the internal layers are localized based on their textural similarities.The proposed method was tested on 23 datasets from two patient groups (glaucoma and normals). The mean unsigned border positioning errors(mean - SD) was 8.52 - 3.13 and 7.56 - 2.95 micrometer for the 2D and 3D methods, respectively.
A Review Paper on Microprocessor Based Controller Programming
Venue: arXiv cs.OH 2012
Year: 2012

Designing of microprocessor based controllers requires specific hardware as well as software programming. Programming depends upon type of the software whether operating software or application software. Programming requires knowledge of system configuration and controller specific programming. Programs are always in digital form so microprocessor can control directly at digital level called Direct Digital Control (DDC).
TV-SVM: Total Variation Support Vector Machine for Semi-Supervised Data Classification
Venue: arXiv cs.LG 2012
Year: 2012

We introduce semi-supervised data classification algorithms based on total variation (TV), Reproducing Kernel Hilbert Space (RKHS), support vector machine (SVM), Cheeger cut, labeled and unlabeled data points. We design binary and multi-class semi-supervised classification algorithms. We compare the TV-based classification algorithms with the related Laplacian-based algorithms, and show that TV classification perform significantly better when the number of labeled data is small.
A Survey of Multibiometric Systems
Venue: arXiv cs.CV 2012
Year: 2012

Most biometric systems deployed in real-world applications are unimodal. Using unimodal biometric systems have to contend with a variety of problems such as: Noise in sensed data; Intra-class variations; Inter-class similarities; Non-universality; Spoof attacks. These problems have addressed by using multibiometric systems, which expected to be more reliable due to the presence of multiple, independent pieces of evidence.
Enhancing Twitter Data Analysis with Simple Semantic Filtering: Example in Tracking Influenza-Like Illnesses
Venue: arXiv cs.SI 2012
Year: 2012

Systems that exploit publicly available user generated content such as Twitter messages have been successful in tracking seasonal influenza. We developed a novel filtering method for Influenza-Like-Illnesses (ILI)-related messages using 587 million messages from Twitter micro-blogs. We first filtered messages based on syndrome keywords from the BioCaster Ontology, an extant knowledge model of laymen's terms. We then filtered the messages according to semantic features such as negation, hashtags, emoticons, humor and geography. The data covered 36 weeks for the US 2009 influenza season from 30th August 2009 to 8th May 2010. Results showed that our system achieved the highest Pearson correlation coefficient of 98.46% (p-value<2.2e-16), an improvement of 3.98% over the previous state-of-the-art method. The results indicate that simple NLP-based enhancements to existing approaches to mine Twitter data can increase the value of this inexpensive resource.
Control Design along Trajectories with Sums of Squares Programming
Venue: arXiv cs.RO 2012
Year: 2012

Motivated by the need for formal guarantees on the stability and safety of controllers for challenging robot control tasks, we present a control design procedure that explicitly seeks to maximize the size of an invariant "funnel" that leads to a predefined goal set. Our certificates of invariance are given in terms of sums of squares proofs of a set of appropriately defined Lyapunov inequalities. These certificates, together with our proposed polynomial controllers, can be efficiently obtained via semidefinite optimization. Our approach can handle time-varying dynamics resulting from tracking a given trajectory, input saturations (e.g. torque limits), and can be extended to deal with uncertainty in the dynamics and state. The resulting controllers can be used by space-filling feedback motion planning algorithms to fill up the space with significantly fewer trajectories. We demonstrate our approach on a severely torque limited underactuated double pendulum (Acrobot) and provide extensive simulation and hardware validation.
Scalable data abstractions for distributed parallel computations
Venue: arXiv cs.PL 2012
Year: 2012

The ability to express a program as a hierarchical composition of parts is an essential tool in managing the complexity of software and a key abstraction this provides is to separate the representation of data from the computation. Many current parallel programming models use a shared memory model to provide data abstraction but this doesn't scale well with large numbers of cores due to non-determinism and access latency. This paper proposes a simple programming model that allows scalable parallel programs to be expressed with distributed representations of data and it provides the programmer with the flexibility to employ shared or distributed styles of data-parallelism where applicable. It is capable of an efficient implementation, and with the provision of a small set of primitive capabilities in the hardware, it can be compiled to operate directly on the hardware, in the same way stack-based allocation operates for subroutines in sequential machines.
Extending OWL-S for the Composition of Web Services Generated With a Legacy Application Wrapper
Venue: arXiv cs.SE 2012
Year: 2012

Despite numerous efforts by various developers, web service composition is still a difficult problem to tackle. Lot of progressive research has been made on the development of suitable standards. These researches help to alleviate and overcome some of the web services composition issues. However, the legacy application wrappers generate nonstandard WSDL which hinder the progress. Indeed, in addition to their lack of semantics, WSDLs have sometimes different shapes because they are adapted to circumvent some technical implementation aspect. In this paper, we propose a method for the semi automatic composition of web services in the context of the NeuroLOG project. In this project the reuse of processing tools relies on a legacy application wrapper called jGASW. The paper describes the extensions to OWL-S in order to introduce and enable the composition of web services generated using the jGASW wrapper and also to implement consistency checks regarding these services.
Elegant Object-oriented Software Design via Interactive, Evolutionary Computation
Venue: arXiv cs.SE 2012
Year: 2012

Design is fundamental to software development but can be demanding to perform. Thus to assist the software designer, evolutionary computing is being increasingly applied using machine-based, quantitative fitness functions to evolve software designs. However, in nature, elegance and symmetry play a crucial role in the reproductive fitness of various organisms. In addition, subjective evaluation has also been exploited in Interactive Evolutionary Computation (IEC). Therefore to investigate the role of elegance and symmetry in software design, four novel elegance measures are proposed based on the evenness of distribution of design elements. In controlled experiments in a dynamic interactive evolutionary computation environment, designers are presented with visualizations of object-oriented software designs, which they rank according to a subjective assessment of elegance. For three out of the four elegance measures proposed, it is found that a significant correlation exists between elegance values and reward elicited. These three elegance measures assess the evenness of distribution of (a) attributes and methods among classes, (b) external couples between classes, and (c) the ratio of attributes to methods. It is concluded that symmetrical elegance is in some way significant in software design, and that this can be exploited in dynamic, multi-objective interactive evolutionary computation to produce elegant software designs.