OpenRaiser/Intern-Atlas huggingface dataset:
Pinning dynamic systems of networks with Markovian switching couplings and controller-node set
Venue: arXiv cs.SY 2014
Year: 2014

In this paper, we study pinning control problem of coupled dynamical systems with stochastically switching couplings and stochastically selected controller-node set. Here, the coupling matrices and the controller-node sets change with time, induced by a continuous-time Markovian chain. By constructing Lyapunov functions, we establish tractable sufficient conditions for exponentially stability of the coupled system. Two scenarios are considered here. First, we prove that if each subsystem in the switching system, i.e. with the fixed coupling, can be stabilized by the fixed pinning controller-node set, and in addition, the Markovian switching is sufficiently slow, then the time-varying dynamical system is stabilized. Second, in particular, for the problem of spatial pinning control of network with mobile agents, we conclude that if the system with the average coupling and pinning gains can be stabilized and the switching is sufficiently fast, the time-varying system is stabilized. Two numerical examples are provided to demonstrate the validity of these theoretical results, including a switching dynamical system between several stable sub-systems, and a dynamical system with mobile nodes and spatial pinning control towards the nodes when these nodes are being in a pre-designed region.
Orthogonal Fault Tolerance for Dynamically Adaptive Systems
Venue: arXiv cs.SE 2014
Year: 2014

In dynamic systems that adapt to users' needs and changing environments, dependability needs cannot be avoided. This paper proposes an orthogonal fault tolerance model as a means to manage and reason about multiple fault tolerance mechanisms that co-exist in dynamically adaptive systems. One of the key challenges associated with dynamically evolving fault tolerance needs is the feature interaction problem arising from the integration of fault tolerance features. The proposed approach provides a separation of fault tolerance concerns to study the effects of integrated fault tolerance on the system. This approach uses state machine and operational semantics to reason about these interactions and inconsistencies. The proposed approach is supported by the tool NuSMV to simulate and verify the state machines against logic statements.
Security Analysis of Cloud Computing
Venue: arXiv cs.CR 2014
Year: 2014

This paper produces a baseline security analysis of the Cloud Computing Operational Environment in terms of threats, vulnerabilities and impacts. An analysis is conducted and the top three threats are identified with recommendations for practitioners. The conclusion of the analysis is that the most serious threats are non-technical and can be solved via management processes rather than technical countermeasures
Conditional Density Estimation with Dimensionality Reduction via Squared-Loss Conditional Entropy Minimization
Venue: arXiv cs.LG 2014
Year: 2014

Regression aims at estimating the conditional mean of output given input. However, regression is not informative enough if the conditional density is multimodal, heteroscedastic, and asymmetric. In such a case, estimating the conditional density itself is preferable, but conditional density estimation (CDE) is challenging in high-dimensional space. A naive approach to coping with high-dimensionality is to first perform dimensionality reduction (DR) and then execute CDE. However, such a two-step process does not perform well in practice because the error incurred in the first DR step can be magnified in the second CDE step. In this paper, we propose a novel single-shot procedure that performs CDE and DR simultaneously in an integrated way. Our key idea is to formulate DR as the problem of minimizing a squared-loss variant of conditional entropy, and this is solved via CDE. Thus, an additional CDE step is not needed after DR. We demonstrate the usefulness of the proposed method through extensive experiments on various datasets including humanoid robot transition and computer art.
Zero-Outage Cellular Downlink with Fixed-Rate D2D Underlay
Venue: arXiv cs.IT 2014
Year: 2014

Two of the emerging trends in wireless cellular systems are Device-to-Device (D2D) and Machine-to-Machine (M2M) communications. D2D enables efficient reuse of the licensed spectrum to support localized transmissions, while M2M connections are often characterized by fixed and low transmission rates. D2D connections can be instrumental in localized aggregation of uplink M2M traffic to a more capable cellular device, before being finally delivered to the Base Station (BS). In this paper we show that a fixed M2M rate is an enabler of efficient Machine-Type D2D underlay operation taking place simultaneously with another \emph{downlink} cellular transmission. In the considered scenario, a BS $B$ transmits to a user $U$, while there are $N_M$ Machine-Type Devices (MTDs) attached to $U$, all sending simultaneously to $U$ and each using the same rate $R_M$. While assuming that $B$ knows the channel $B-U$, but not the interfering channels from the MTDs to $U$, we prove that there is a positive downlink rate that can always be decoded by $U$, leading to zero-outage of the downlink signal. This is a rather surprising consequence of the features of the multiple access channel and the fixed rate $R_M$. We also consider the case of a simpler, single-user decoder at $U$ with successive interference cancellation. However, with single-user decoder, a positive zero-outage rate exists only when $N_M=1$ and is zero when $N_M>1$. This implies that joint decoding is instrumental in enabling fixed-rate underlay operation.
Partially Punctual Metric Temporal Logic is Decidable
Venue: arXiv cs.LO 2014
Year: 2014

Metric Temporal Logic $\mathsf{MTL}[\until_I,\since_I]$ is one of the most studied real time logics. It exhibits considerable diversity in expressiveness and decidability properties based on the permitted set of modalities and the nature of time interval constraints $I$. Henzinger et al., in their seminal paper showed that the non-punctual fragment of $\mathsf{MTL}$ called $\mathsf{MITL}$ is decidable. In this paper, we sharpen this decidability result by showing that the partially punctual fragment of $\mathsf{MTL}$ (denoted $\mathsf{PMTL}$) is decidable over strictly monotonic finite point wise time. In this fragment, we allow either punctual future modalities, or punctual past modalities, but never both together. We give two satisfiability preserving reductions from $\mathsf{PMTL}$ to the decidable logic $\mathsf{MTL}[\until_I]$. The first reduction uses simple projections, while the second reduction uses a novel technique of temporal projections with oversampling. We study the trade-off between the two reductions: while the second reduction allows the introduction of extra action points in the underlying model, the equisatisfiable $\mathsf{MTL}[\until_I]$ formula obtained is exponentially succinct than the one obtained via the first reduction, where no oversampling of the underlying model is needed. We also show that $\mathsf{PMTL}$ is strictly more expressive than the fragments $\mathsf{MTL}[\until_I,\since]$ and $\mathsf{MTL}[\until,\since_I]$.
Super-resolution Line Spectrum Estimation with Block Priors
Venue: arXiv cs.IT 2014
Year: 2014

We address the problem of super-resolution line spectrum estimation of an undersampled signal with block prior information. The component frequencies of the signal are assumed to take arbitrary continuous values in known frequency blocks. We formulate a general semidefinite program to recover these continuous-valued frequencies using theories of positive trigonometric polynomials. The proposed semidefinite program achieves super-resolution frequency recovery by taking advantage of known structures of frequency blocks. Numerical experiments show great performance enhancements using our method.
Editorial for the Bibliometric-enhanced Information Retrieval Workshop at ECIR 2014
Venue: arXiv cs.IR 2014
Year: 2014

This first "Bibliometric-enhanced Information Retrieval" (BIR 2014) workshop aims to engage with the IR community about possible links to bibliometrics and scholarly communication. Bibliometric techniques are not yet widely used to enhance retrieval processes in digital libraries, although they offer value-added effects for users. In this workshop we will explore how statistical modelling of scholarship, such as Bradfordizing or network analysis of co-authorship network, can improve retrieval services for specific communities, as well as for large, cross-domain collections. This workshop aims to raise awareness of the missing link between information retrieval (IR) and bibliometrics / scientometrics and to create a common ground for the incorporation of bibliometric-enhanced services into retrieval at the digital library interface. Our interests include information retrieval, information seeking, science modelling, network analysis, and digital libraries. The goal is to apply insights from bibliometrics, scientometrics, and informetrics to concrete practical problems of information retrieval and browsing.
Structural Group Sparse Representation for Image Compressive Sensing Recovery
Venue: arXiv cs.CV 2014
Year: 2014

Compressive Sensing (CS) theory shows that a signal can be decoded from many fewer measurements than suggested by the Nyquist sampling theory, when the signal is sparse in some domain. Most of conventional CS recovery approaches, however, exploited a set of fixed bases (e.g. DCT, wavelet, contourlet and gradient domain) for the entirety of a signal, which are irrespective of the nonstationarity of natural signals and cannot achieve high enough degree of sparsity, thus resulting in poor rate-distortion performance. In this paper, we propose a new framework for image compressive sensing recovery via structural group sparse representation (SGSR) modeling, which enforces image sparsity and self-similarity simultaneously under a unified framework in an adaptive group domain, thus greatly confining the CS solution space. In addition, an efficient iterative shrinkage/thresholding algorithm based technique is developed to solve the above optimization problem. Experimental results demonstrate that the novel CS recovery strategy achieves significant performance improvements over the current state-of-the-art schemes and exhibits nice convergence.
Meteorological time series forecasting based on MLP modelling using heterogeneous transfer functions
Venue: arXiv cs.LG 2014
Year: 2014

In this paper, we propose to study four meteorological and seasonal time series coupled with a multi-layer perceptron (MLP) modeling. We chose to combine two transfer functions for the nodes of the hidden layer, and to use a temporal indicator (time index as input) in order to take into account the seasonal aspect of the studied time series. The results of the prediction concern two years of measurements and the learning step, eight independent years. We show that this methodology can improve the accuracy of meteorological data estimation compared to a classical MLP modelling with a homogenous transfer function.
Cramer Rao Lower Bound for Underwater Range Estimation with Noisy Sound Speed Profile
Venue: arXiv cs.IT 2014
Year: 2014

In this paper, the Cramer Rao bound (CRB) for range estimation between two underwater nodes is calculated under a Gaussian noise assumption on the measurements. The nodes can measure their depths, their mutual time of flight, and they have access to noisy sound speed samples at different depths. The effect of each measurement on the CRB will be analyzed, and it will be shown that for long distances, the effect of the sound speed measurement noise is dominant, and its impact depends on the positions of the nodes, actual sound speed profile, the number of sound speed samples, and the depths at which the sound speed samples are gathered.
Open induction in a bounded arithmetic for TC^0
Venue: arXiv cs.LO 2014
Year: 2014

The elementary arithmetic operations $+,\cdot,\le$ on integers are well-known to be computable in the weak complexity class $\mathrm{TC}^0$, and it is a basic question what properties of these operations can be proved using only $\mathrm{TC}^0$-computable objects, i.e., in a theory of bounded arithmetic corresponding to $\mathrm{TC}^0$. We will show that the theory $\mathit{VTC}^0$ extended with an axiom postulating the totality of iterated multiplication (which is computable in $\mathrm{TC}^0$) proves induction for quantifier-free formulas in the language $\langle +,\cdot,\le \rangle$ (IOpen), and more generally, minimization for $Σ^b_0$ formulas in the language of Buss's $S_2$.
Implementing spectral methods for hidden Markov models with real-valued emissions
Venue: arXiv cs.LG 2014
Year: 2014

Hidden Markov models (HMMs) are widely used statistical models for modeling sequential data. The parameter estimation for HMMs from time series data is an important learning problem. The predominant methods for parameter estimation are based on local search heuristics, most notably the expectation-maximization (EM) algorithm. These methods are prone to local optima and oftentimes suffer from high computational and sample complexity. Recent years saw the emergence of spectral methods for the parameter estimation of HMMs, based on a method of moments approach. Two spectral learning algorithms as proposed by Hsu, Kakade and Zhang 2012 (arXiv:0811.4413) and Anandkumar, Hsu and Kakade 2012 (arXiv:1203.0683) are assessed in this work. Using experiments with synthetic data, the algorithms are compared with each other. Furthermore, the spectral methods are compared to the Baum-Welch algorithm, a well-established method applying the EM algorithm to HMMs. The spectral algorithms are found to have a much more favorable computational and sample complexity. Even though the algorithms readily handle high dimensional observation spaces, instability issues are encountered in this regime. In view of learning from real-world experimental data, the representation of real-valued observations for the use in spectral methods is discussed, presenting possible methods to represent data for the use in the learning algorithms.
Secure Degrees of Freedom Regions of Multiple Access and Interference Channels: The Polytope Structure
Venue: arXiv cs.IT 2014
Year: 2014

The sum secure degrees of freedom (s.d.o.f.) of two fundamental multi-user network structures, the K-user Gaussian multiple access (MAC) wiretap channel and the K-user interference channel (IC) with secrecy constraints, have been determined recently as K(K-1)/(K(K-1)+1) [1,2] and K(K-1)/(2K-1) [3,4], respectively. In this paper, we determine the entire s.d.o.f. regions of these two channel models. The converse for the MAC follows from a middle step in the converse of [1,2]. The converse for the IC includes constraints both due to secrecy as well as due to interference. Although the portion of the region close to the optimum sum s.d.o.f. point is governed by the upper bounds due to secrecy constraints, the other portions of the region are governed by the upper bounds due to interference constraints. Different from the existing literature, in order to fully understand the characterization of the s.d.o.f. region of the IC, one has to study the 4-user case, i.e., the 2 or 3-user cases do not illustrate the generality of the problem. In order to prove the achievability, we use the polytope structure of the converse region. In both MAC and IC cases, we develop explicit schemes that achieve the extreme points of the polytope region given by the converse. Specifically, the extreme points of the MAC region are achieved by an m-user MAC wiretap channel with (K-m) helpers, i.e., by setting (K-m) users' secure rates to zero and utilizing them as pure (structured) cooperative jammers. The extreme points of the IC region are achieved by a (K-m)-user IC with confidential messages, m helpers, and N external eavesdroppers, for m>=1 and a finite N. A byproduct of our results in this paper is that the sum s.d.o.f. is achieved only at one extreme point of the s.d.o.f. region, which is the symmetric-rate extreme point, for both MAC and IC channel models.
A formal approach for correct-by-construction system substitution
Venue: arXiv cs.SE 2014
Year: 2014

The substitution of a system with another one may occur in several situations like system adaptation, system failure management, system resilience, system reconfiguration, etc. It consists in replacing a running system by another one when given conditions hold. This contribution summarizes our proposal to define a formal setting for proving the correctness of system substitution. It relies on refinement and on the Event-B method.
Critical Infrastructure Protection: having SIEM technology cope with network heterogeneity
Venue: arXiv cs.CR 2014
Year: 2014

Coordinated and targeted cyber-attacks to Critical Infrastructures (CIs) are becoming more and more frequent and sophisticated. This is due to: i) the recent technology shift towards Commercial Off-The-Shelf (COTS) products, and ii) new economical and socio-political motivations. In this paper, we discuss some of the most relevant security issues resulting from the adoption in CIs of heterogeneous network infrastructures (specifically combining wireless and IP trunks), and suggest techniques to detect, as well as to counter/mitigate attacks. We claim that techniques such as those we propose here should be integrated in future SIEM (Security Information and Event Management) solutions, and we discuss how we have done so in the EC-funded MASSIF project, with respect to a real-world CI scenario, specifically a distributed system for power grid monitoring.
Detection in Analog Sensor Networks with a Large Scale Antenna Fusion Center
Venue: arXiv cs.IT 2014
Year: 2014

We consider the distributed detection of a zero-mean Gaussian signal in an analog wireless sensor network with a fusion center (FC) configured with a large number of antennas. The transmission gains of the sensor nodes are optimized by minimizing the ratio of the log probability of detection (PD) and log probability of false alarm (PFA). We show that the problem is convex with respect to the squared norm of the transmission gains, and that a closed-form solution can be found using the Karush-Kuhn-Tucker conditions. Our results indicate that a constant PD can be maintained with decreasing sensor transmit gain provided that the number of antennas increases at the same rate. This is contrasted with the case of a single-antenna FC, where PD is monotonically decreasing with transmit gain. On the other hand, we show that when the transmit power is high, the single- and multi-antenna FC both asymptotically achieve the same PD upper bound.
An Optimal Offline Algorithm for List Update
Venue: arXiv cs.DS 2014
Year: 2014

For the static list update problem, given an ordered list $ρ_0$ (an ordering of the list $L$ = \{ $a_a, a_2, ..., a_l$ \}), and a sequence $σ= (σ_1, σ_2, ..., σ_m)$ of requests for items in $L$, we characterize the list reorganizations in an optimal offline solution in terms of an initial permutation of the list followed by a sequence of $m$ {\em element transfers}, where an element transfer is a type of list reorganization where only the requested item can be moved. Then we make use of this characterization to design an $O(l^{2} (l-1)!m)$ time optimal offline algorithm.
Analysis-by-Synthesis Quantization for Compressed Sensing Measurements
Venue: arXiv cs.IT 2014
Year: 2014

We consider a resource-limited scenario where a sensor that uses compressed sensing (CS) collects a low number of measurements in order to observe a sparse signal, and the measurements are subsequently quantized at a low bit-rate followed by transmission or storage. For such a scenario, we design new algorithms for source coding with the objective of achieving good reconstruction performance of the sparse signal. Our approach is based on an analysis-by-synthesis principle at the encoder, consisting of two main steps: (1) the synthesis step uses a sparse signal reconstruction technique for measuring the direct effect of quantization of CS measurements on the final sparse signal reconstruction quality, and (2) the analysis step decides appropriate quantized values to maximize the final sparse signal reconstruction quality. Through simulations, we compare the performance of the proposed quantization algorithms vis-a-vis existing quantization schemes.
An argumentation system for reasoning with conflict-minimal paraconsistent ALC
Venue: arXiv cs.AI 2014
Year: 2014

The semantic web is an open and distributed environment in which it is hard to guarantee consistency of knowledge and information. Under the standard two-valued semantics everything is entailed if knowledge and information is inconsistent. The semantics of the paraconsistent logic LP offers a solution. However, if the available knowledge and information is consistent, the set of conclusions entailed under the three-valued semantics of the paraconsistent logic LP is smaller than the set of conclusions entailed under the two-valued semantics. Preferring conflict-minimal three-valued interpretations eliminates this difference. Preferring conflict-minimal interpretations introduces non-monotonicity. To handle the non-monotonicity, this paper proposes an assumption-based argumentation system. Assumptions needed to close branches of a semantic tableaux form the arguments. Stable extensions of the set of derived arguments correspond to conflict minimal interpretations and conclusions entailed by all conflict-minimal interpretations are supported by arguments in all stable extensions.
Massive MIMO with 1-bit ADC
Venue: arXiv cs.IT 2014
Year: 2014

We investigate massive multiple-input-multiple output (MIMO) uplink systems with 1-bit analog-to-digital converters (ADCs) on each receiver antenna. Receivers that rely on 1-bit ADC do not need energy-consuming interfaces such as automatic gain control (AGC). This decreases both ADC building and operational costs. Our design is based on maximal ratio combining (MRC), zero-forcing (ZF), and least squares (LS) detection, taking into account the effects of the 1-bit ADC on channel estimation. Through numerical results, we show good performance of the system in terms of mutual information and symbol error rate (SER). Furthermore, we provide an analytical approach to calculate the mutual information and SER of the MRC receiver. The analytical approach reduces complexity in the sense that a symbol and channel noise vectors Monte Carlo simulation is avoided.