OpenRaiser/Intern-Atlas huggingface dataset:
Impact of Radar and Communication Coexistence on Radar's Detectable Target Parameters
Venue: arXiv cs.NI 2014
Year: 2014

In this paper, we present our spectrum sharing algorithm between a multi-input multi-output (MIMO) radar and Long Term Evolution (LTE) cellular system with multiple base stations (BS)s. We analyze the performance of MIMO radars in detecting the angle of arrival, propagation delay and Doppler angular frequency by projecting orthogonal waveforms onto the null-space of interference channel matrix. We compare and analyze the radar's detectable target parameters in the case of the original radar waveform and the case of null-projected radar waveform. Our proposed spectrum-sharing algorithm causes minimum loss in radar performance by selecting the best interference channel that does not cause interference to the i'th LTE base station due to the radar signal. We show through our analytical and simulation results that the loss in the radar performance in detecting the target parameters is minimal when our proposed spectrum sharing algorithm is used to select the best channel onto which radar signals are projected.
Scalability and Resilience of Software-Defined Networking: An Overview
Venue: arXiv cs.NI 2014
Year: 2014

Software-Defined Networking (SDN) allows to control the available network resources by an intelligent and centralized authority in order to optimize traffic flows in a flexible manner. However, centralized control may face scalability issues when the network size or the number of traffic flows increases. Also, a centralized controller may form a single point of failure, thereby affecting the network resilience. This article provides an overview of SDN that focuses on (1) scalability concerning the increased control overhead faced by a central controller, and (2) resiliency in terms of protection against controller failure, network topology failure and security in terms of malicious attacks.
Binary matrices of optimal autocorrelations as alignment marks
Venue: arXiv cs.CV 2014
Year: 2014

We define a new class of binary matrices by maximizing the peak-sidelobe distances in the aperiodic autocorrelations. These matrices can be used as robust position marks for in-plane spatial alignment. The optimal square matrices of dimensions up to 7 by 7 and optimal diagonally-symmetric matrices of 8 by 8 and 9 by 9 were found by exhaustive searches.
Non-existence of a ternary constant weight $(16, 5, 15; 2048)$ diameter perfect code
Venue: arXiv cs.IT 2014
Year: 2014

Ternary constant weight codes of length $n=2^m$, weight $n-1$, cardinality $2^n$ and distance $5$ are known to exist for every $m$ for which there exists an APN permutation of order $2^m$, that is, at least for all odd $m \geq 3$ and for $m=6$. We show the non-existence of such codes for $m=4$ and prove that any codes with the parameters above are diameter perfect.
Fast Disk Conformal Parameterization of Simply-connected Open Surfaces
Venue: arXiv cs.CG 2014
Year: 2014

Surface parameterizations have been widely used in computer graphics and geometry processing. In particular, as simply-connected open surfaces are conformally equivalent to the unit disk, it is desirable to compute the disk conformal parameterizations of the surfaces. In this paper, we propose a novel algorithm for the conformal parameterization of a simply-connected open surface onto the unit disk, which significantly speeds up the computation, enhances the conformality and stability, and guarantees the bijectivity. The conformality distortions at the inner region and on the boundary are corrected by two steps, with the aid of an iterative scheme using quasi-conformal theories. Experimental results demonstrate the effectiveness of our proposed method.
Truncated Moment Problem for Dirac Mixture Densities with Entropy Regularization
Venue: arXiv cs.SY 2014
Year: 2014

We assume that a finite set of moments of a random vector is given. Its underlying density is unknown. An algorithm is proposed for efficiently calculating Dirac mixture densities maintaining these moments while providing a homogeneous coverage of the state space.
Computing Classic Closeness Centrality, at Scale
Venue: arXiv cs.DS 2014
Year: 2014

Closeness centrality, first considered by Bavelas (1948), is an importance measure of a node in a network which is based on the distances from the node to all other nodes. The classic definition, proposed by Bavelas (1950), Beauchamp (1965), and Sabidussi (1966), is (the inverse of) the average distance to all other nodes. We propose the first highly scalable (near linear-time processing and linear space overhead) algorithm for estimating, within a small relative error, the classic closeness centralities of all nodes in the graph. Our algorithm applies to undirected graphs, as well as for centrality computed with respect to round-trip distances in directed graphs. For directed graphs, we also propose an efficient algorithm that approximates generalizations of classic closeness centrality to outbound and inbound centralities. Although it does not provide worst-case theoretical approximation guarantees, it is designed to perform well on real networks. We perform extensive experiments on large networks, demonstrating high scalability and accuracy.
An Experimental Study of Cryptography Capability using Chained Key Exchange Scheme for Embedded Devices
Venue: arXiv cs.CR 2014
Year: 2014

After 38 years of birthday Diffie-Hellman Key Exchange (DHKE), there are many proposed improvements in the DHKE protocol to encounter modern security issues. This protocol seems quite simple to be implemented, but it can be vulnerable to many types of attacks. In this work, we propose the Chained Key Exchange scheme as a case study to explore cryptographic computation capability of embedded microcontroller. We choose ARM RaspberryPi board as hardware platform for experimental setup. To enable RasberberryPi system on chip (SoC) to perform cryptographic computation, we modified the GNU GMP Bignum library to support a simple primitive cryptographic computation in the UBOOT firmware. The main purpose of our study is to determine whether there is any gap between cryptographic protocol-scheme (in term of theoretical) and its engineering implementation. Our scheme will be integrated with Trivial File Transfer Protocol (TFTP) application in the UBOOT firmware. Our proposed scheme in the TFTP protocol will secure the sharing of secrets and symmetric keys (e.g., AES256). After that, the symmetric encryption algorithm can be used to encrypt data in the cases of remote system updates, patching and upgrades (e.g., firmware, kernel or application).
Sparse Coding on Symmetric Positive Definite Manifolds using Bregman Divergences
Venue: arXiv cs.CV 2014
Year: 2014

This paper introduces sparse coding and dictionary learning for Symmetric Positive Definite (SPD) matrices, which are often used in machine learning, computer vision and related areas. Unlike traditional sparse coding schemes that work in vector spaces, in this paper we discuss how SPD matrices can be described by sparse combination of dictionary atoms, where the atoms are also SPD matrices. We propose to seek sparse coding by embedding the space of SPD matrices into Hilbert spaces through two types of Bregman matrix divergences. This not only leads to an efficient way of performing sparse coding, but also an online and iterative scheme for dictionary learning. We apply the proposed methods to several computer vision tasks where images are represented by region covariance matrices. Our proposed algorithms outperform state-of-the-art methods on a wide range of classification tasks, including face recognition, action recognition, material classification and texture categorization.
Kernel Coding: General Formulation and Special Cases
Venue: arXiv cs.CV 2014
Year: 2014

Representing images by compact codes has proven beneficial for many visual recognition tasks. Most existing techniques, however, perform this coding step directly in image feature space, where the distributions of the different classes are typically entangled. In contrast, here, we study the problem of performing coding in a high-dimensional Hilbert space, where the classes are expected to be more easily separable. To this end, we introduce a general coding formulation that englobes the most popular techniques, such as bag of words, sparse coding and locality-based coding, and show how this formulation and its special cases can be kernelized. Importantly, we address several aspects of learning in our general formulation, such as kernel learning, dictionary learning and supervised kernel coding. Our experimental evaluation on several visual recognition tasks demonstrates the benefits of performing coding in Hilbert space, and in particular of jointly learning the kernel, the dictionary and the classifier.
Multi-Use Multi-Secret Sharing Scheme for General Access Structure
Venue: arXiv cs.CR 2014
Year: 2014

The main aim of this paper is to construct a multi-secret sharing scheme for general access structure in a trusted dealer model using suitable hash function and Lagrange's interpolation method. Even though, the proposed scheme is a multi-secret and multi-use one, each participant has to carry only one share. The suitable use of collision resistant one way hash function makes the scheme efficient and multi-use. Moreover, the scheme has a nice property that secrets, participants or qualified sets of participants may be added to or even may be made inactive dynamically by the dealer to get a new access structure without altering the shares of the existing participants in the old access structure. Finally, in the proposed scheme, both the combiner and the share holders can verify the correctness of the information that they are receiving from each other.
Marginalizing over the PageRank Damping Factor
Venue: arXiv cs.IR 2014
Year: 2014

In this note, we show how to marginalize over the damping parameter of the PageRank equation so as to obtain a parameter-free version known as TotalRank. Our discussion is meant as a reference and intended to provide a guided tour towards an interesting result that has applications in information retrieval and classification.
A Computational Approach to Bisimulation of Hybrid Dynamical Systems
Venue: arXiv cs.SY 2014
Year: 2014

The problem of finding a finite state symbolic model which is bisimilar to a hybrid dynamical system (HDS) and has the minimum number of states is considered. The considered class of HDS allows for discrete-valued inputs that only affect the jumps (events) of the HDS. Representation of the HDS in the form of a transition system is revisited in comparison with prior works. An algorithm is proposed for solving the problem which gives the bisimulation with the minimum number of states if it already exists and also a parameter of the algorithm is properly tuned. There is no need for stability assumptions and no time discretization is applied. The results are applied to an example
Who creates trends in online social media: The crowd or opinion leaders?
Venue: arXiv cs.SI 2014
Year: 2014

Trends in online social media always reflect the collective attention of a vast number of individuals across the network. For example, Internet slang words can be ubiquitous because of social memes and online contagions in an extremely short period. From Weibo, a Twitter-like service in China, we find that the adoption of popular Internet slang words experiences two peaks in its temporal evolution, in which the former is relatively much lower than the latter. This interesting phenomenon in fact provides a decent window to disclose essential factors that drive the massive diffusion underlying trends in online social media. Specifically, the in-depth comparison between diffusions represented by different peaks suggests that more attention from the crowd at early stage of the propagation produces large-scale coverage, while the dominant participation of opinion leaders at the early stage just leads to popularity of small scope. Our results quantificationally challenge the conventional hypothesis of influentials. And the implications of these novel findings for marketing practice and influence maximization in social networks are also discussed.
Empirical Evaluation of Tree distances for Parser Evaluation
Venue: arXiv cs.CL 2014
Year: 2014

In this empirical study, I compare various tree distance measures -- originally developed in computational biology for the purpose of tree comparison -- for the purpose of parser evaluation. I will control for the parser setting by comparing the automatically generated parse trees from the state-of-the-art parser Charniak, 2000) with the gold-standard parse trees. The article describes two different tree distance measures (RF and QD) along with its variants (GRF and GQD) for the purpose of parser evaluation. The article will argue that RF measure captures similar information as the standard EvalB metric (Sekine and Collins, 1997) and the tree edit distance (Zhang and Shasha, 1989) applied by Tsarfaty et al. (2011). Finally, the article also provides empirical evidence by reporting high correlations between the different tree distances and EvalB metric's scores.
A Requirements Modeling Language for the Component Behavior of Cyber Physical Robotics Systems
Venue: arXiv cs.SE 2014
Year: 2014

Software development for robotics applications is a sophisticated endeavor as robots are inherently complex. Explicit modeling of the architecture and behavior of robotics application yields many advantages to cope with this complexity by identifying and separating logically and physically independent components and by hierarchically structuring the system under development. On top of component and connector models we propose modeling the requirements on the behavior of robotics software components using I/O! automata. This approach facilitates early simulation of requirements model, allows to subject these to formal analysis and to generate the software from them. In this paper, we introduce an extension of the architecture description language MontiArc to model the requirements on components with I/O!automata, which are defined in the spirit of Martin Glinz Statecharts for requirements modeling [10]. We furthermore present a case study based on a robotics application generated for the Lego NXT robotic platform.
Near optimal compressed sensing without priors: Parametric SURE Approximate Message Passing
Venue: arXiv cs.IT 2014
Year: 2014

Both theoretical analysis and empirical evidence confirm that the approximate message passing (AMP) algorithm can be interpreted as recursively solving a signal denoising problem: at each AMP iteration, one observes a Gaussian noise perturbed original signal. Retrieving the signal amounts to a successive noise cancellation until the noise variance decreases to a satisfactory level. In this paper we incorporate the Stein's unbiased risk estimate (SURE) based parametric denoiser with the AMP framework and propose the novel parametric SURE-AMP algorithm. At each parametric SURE-AMP iteration, the denoiser is adaptively optimized within the parametric class by minimizing SURE, which depends purely on the noisy observation. In this manner, the parametric SURE-AMP is guaranteed with the best-in-class recovery and convergence rate. If the parameter family includes the families of the mimimum mean squared error (MMSE) estimators, we are able to achieve the Bayesian optimal AMP performance without knowing the signal prior. In the paper, we resort to the linear parameterization of the SURE based denoiser and propose three different kernel families as the base functions. Numerical simulations with the Bernoulli-Gaussian, $k$-dense and Student's-t signals demonstrate that the parametric SURE-AMP does not only achieve the state-of-the-art recovery but also runs more than 20 times faster than the EM-GM-GAMP algorithm.
On Cooperative Multiple Access Channels with Delayed CSI at Transmitters
Venue: arXiv cs.IT 2014
Year: 2014

We consider a cooperative two-user multiaccess channel in which the transmission is controlled by a random state. Both encoders transmit a common message and, one of the encoders also transmits an individual message. We study the capacity region of this communication model for different degrees of availability of the states at the encoders, causally or strictly causally. In the case in which the states are revealed causally to both encoders but not to the decoder we find an explicit characterization of the capacity region in the discrete memoryless case. In the case in which the states are revealed only strictly causally to both encoders, we establish inner and outer bounds on the capacity region. The outer bound is non-trivial, and has a relatively simple form. It has the advantage of incorporating only one auxiliary random variable. We then introduce a class of cooperative multiaccess channels with states known strictly causally at both encoders for which the inner and outer bounds agree; and so we characterize the capacity region for this class. In this class of channels, the state can be obtained as a deterministic function of the channel inputs and output. We also study the model in which the states are revealed, strictly causally, in an asymmetric manner, to only one encoder. Throughout the paper, we discuss a number of examples; and compute the capacity region of some of these examples. The results shed more light on the utility of delayed channel state information for increasing the capacity region of state-dependent cooperative multiaccess channels; and tie with recent progress in this framework.
Experiments on Data Preprocessing of Persian Blog Networks
Venue: arXiv cs.SI 2014
Year: 2014

Social networks analysis and exploring is important for researchers, sociologists, academics, and various businesses due to their information potential. Because of the large volume, diversity, and the data growth rate in web 2.0, some challenges have been made in these data analysis. Based on definitions, weblogs are a form of social networking. So far, the majority of studies and researches in the field of weblog networks analysis and exploring their stored data have been based on international data sets. In this paper, a framework for preprocessing and data analysis in weblog networks is presented and the results of applying it on a Persian weblog network, as a case study, are expressed.
Modeling, Stability Analysis, and Testing of a Hybrid Docking Simulator
Venue: arXiv cs.OH 2014
Year: 2014

A hybrid docking simulator is a hardware-in-the-loop (HIL) simulator that includes a hardware element within a numerical simulation loop. One of the goals of performing a HIL simulation at the European Proximity Operation Simulator (EPOS) is the verification and validation of the docking phase in an on-orbit servicing mission.....
Faster Information Propagation on Highways: a Virtual MIMO Approach
Venue: arXiv cs.IT 2014
Year: 2014

In vehicular communications, traffic-related information should be spread over the network as quickly as possible to maintain a safe and reliable transportation system. This motivates us to develop more efficient information propagation schemes. In this paper, we propose a novel cluster-based cooperative information forwarding scheme, in which the vehicles opportunistically form virtual antenna arrays to boost one-hop transmission range and therefore accelerate information propagation along the highway. Both closed-form results of the transmission range gain and the improved Information Propagation Speed (IPS) are derived and verified by simulations. It is observed that the proposed scheme demonstrates the most significant IPS gain in moderate traffic scenarios, whereas too dense or too sparse vehicle density results in less gain. Moreover, it is also shown that increased mobility offers more contact opportunities and thus facilitates information propagation.
Modelling Electrical Car Diffusion Based on Agents
Venue: arXiv cs.MA 2014
Year: 2014

Replacing traditional fossil fuel vehicles with innovative zero-emission vehicles for the transport in ci ties is one of the major tactics to achieve the UK government 2020 target of cutting emission. We are developing an agent-based simulation model to study the possible impact of different governmental interventions on the diffusion of such vehicles. Options that could be studied with our what-if analysis to include things like car parking charges, price of electrical car, energy awareness and word of mouth. In this paper we present a first case study related to the introduction of a new car park charging scheme at the University of Nottingham. We have developed an agent based model to simulate theimpact of different car parking rates and other incentives on the uptake of electrical cars. The goal of this case study is to demonstrate the usefulness of agent-based modelling and simulation for such investigations.
Friendly Artificial Intelligence: the Physics Challenge
Venue: arXiv cs.CY 2014
Year: 2014

Relentless progress in artificial intelligence (AI) is increasingly raising concerns that machines will replace humans on the job market, and perhaps altogether. Eliezer Yudkowski and others have explored the possibility that a promising future for humankind could be guaranteed by a superintelligent "Friendly AI", designed to safeguard humanity and its values. I argue that, from a physics perspective where everything is simply an arrangement of elementary particles, this might be even harder than it appears. Indeed, it may require thinking rigorously about the meaning of life: What is "meaning" in a particle arrangement? What is "life"? What is the ultimate ethical imperative, i.e., how should we strive to rearrange the particles of our Universe and shape its future? If we fail to answer the last question rigorously, this future is unlikely to contain humans.
CoMOGrad and PHOG: From Computer Vision to Fast and Accurate Protein Tertiary Structure Retrieval
Venue: arXiv cs.CV 2014
Year: 2014

Due to the advancements in technology number of entries in the structural database of proteins are increasing day by day. Methods for retrieving protein tertiary structures from this large database is the key to comparative analysis of structures which plays an important role to understand proteins and their function. In this paper, we present fast and accurate methods for the retrieval of proteins from a large database with tertiary structures similar to a query protein. Our proposed methods borrow ideas from the field of computer vision. The speed and accuracy of our methods comes from the two newly introduced features, the co-occurrence matrix of the oriented gradient and pyramid histogram of oriented gradient and from the use of Euclidean distance as the distance measure. Experimental results clearly indicate the superiority of our approach in both running time and accuracy. Our method is readily available for use from this website: http://research.buet.ac.bd:8080/Comograd/.
Deontic modality based on preference
Venue: arXiv cs.LO 2014
Year: 2014

Deontic modalities are here defined in terms of the preference relation explored in our previous work (Osherson and Weinstein, 2012). Some consequences of the system are discussed.
A Supervisory Control Approach to Dynamic Cyber-Security
Venue: arXiv cs.SY 2014
Year: 2014

An analytical approach for a dynamic cyber-security problem that captures progressive attacks to a computer network is presented. We formulate the dynamic security problem from the defender's point of view as a supervisory control problem with imperfect information, modeling the computer network's operation by a discrete event system. We consider a min-max performance criterion and use dynamic programming to determine, within a restricted set of policies, an optimal policy for the defender. We study and interpret the behavior of this optimal policy as we vary certain parameters of the supervisory control problem.