Robust Detection of Incumbents in Cognitive Radio Networks Using Groups

Cognitive radio is a wireless technology aimed at improvingthe efficiency use of the radio-electric spectrum, thus facilitating a reductionin the load on the free frequency bands. Cognitive radio networkscan scan the spectrum and adapt their parameters to operate in the unoccupiedbands. To avoid interfering with licensed users operating on a givenchannel, the networks need to be highly sensitive, which is achieved byusing cooperative sensing methods. Current cooperative sensing methodsare not robust enough against occasional or continuous attacks. This articleoutlines a Group Fusion method that takes into account the behavior ofusers over the short and long term. On fusing the data, the method is basedon giving more weight to user groups that are more unanimous in their decisions.Simulations have been performed in a dynamic environment withinterferences. Results prove that when attackers are present (both reiterativeor sporadic), the proposed Group Fusion method has superior sensingcapability than other methods.

High capacity robust audio watermarking scheme based on FFT and linear regression

Peer-reviewed

A robust audio watermarking scheme based on MPEG 1 Layer 3 Compression

This paper describes an audio watermarking scheme based on lossy compression. The main idea is taken from an image watermarking approach where the JPEG compression algorithm is used to determine where and how the mark should be placed. Similarly, in the audio scheme suggested in this paper, an MPEG 1 Layer 3 algorithm is chosen for compression to determine the position of the mark bits and, thus, the psychoacoustic masking of the MPEG 1 Layer 3compression is implicitly used. This methodology provides with a high robustness degree against compression attacks. The suggested scheme is also shown to succeed against most of the StirMark benchmark attacks for audio.

Robust power allocation algorithms for MIMO OFDM systems with imperfect CSI

This paper presents a Bayesian approach to the design of transmit prefiltering matrices in closed-loop schemes robust to channel estimation errors. The algorithms are derived for a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system. Two different optimizationcriteria are analyzed: the minimization of the mean square error and the minimization of the bit error rate. In both cases, the transmitter design is based on the singular value decomposition (SVD) of the conditional mean of the channel response, given the channel estimate. The performance of the proposed algorithms is analyzed,and their relationship with existing algorithms is indicated. As withother previously proposed solutions, the minimum bit error rate algorithmconverges to the open-loop transmission scheme for very poor CSI estimates.

Robust beamforming for interference rejection in mobile communications

The problem of robust beamformer design for mobile communicationsapplications in the presence of moving co-channel sources isaddressed. A generalization of the optimum beamformer based on a statisticalmodel accounting for source movement is proposed. The new methodis easily implemented and is shown to offer dramatic improvements overconventional optimum beamforming for moving sources under a varietyof operating conditions.

Unexplored aspects of bureaucratic autonomy: a state of the field and ways forward

This article first provides a selective overview of the literature on bureaucratic autonomy and identifies different approaches to this topic. The second section discusses three major sets of open questions, which will be tackled in the contributions to this special issue: the subjective, dynamic and relational nature of autonomy; the complex linkages between tasks, organizational forms, and national path dependencies on the one hand and autonomy and performance on the other hand; and the interplay between autonomy, accountability and democratic legitimacy.

Robust Estimators of the Generalized Log-Gamma Distribution

We propose robust estimators of the generalized log-gamma distribution and, more generally, of location-shape-scale families of distributions. A (weighted) Q tau estimator minimizes a tau scale of the differences between empirical and theoretical quantiles. It is n(1/2) consistent; unfortunately, it is not asymptotically normal and, therefore, inconvenient for inference. However, it is a convenient starting point for a one-step weighted likelihood estimator, where the weights are based on a disparity measure between the model density and a kernel density estimate. The one-step weighted likelihood estimator is asymptotically normal and fully efficient under the model. It is also highly robust under outlier contamination. Supplementary materials are available online.

Assessing positive mental health in people with chronic physical health problems: correlations with socio-demographic variables and physical health status

Background: A holistic perspective on health implies giving careful consideration to the relationship between physical and mental health. In this regard the present study sought to determine the level of Positive Mental Health (PMH) among people with chronic physical health problems, and to examine the relationship between the observed levels of PMH and both physical health status and socio-demographic variables. Methods: The study was based on the Multifactor Model of Positive Mental Health (Lluch, 1999), which comprises six factors: Personal Satisfaction (F1), Prosocial Attitude (F2), Self-control (F3), Autonomy (F4), Problem-solving and Self-actualization (F5), and Interpersonal Relationship Skills (F6). The sample comprised 259 adults with chronic physical health problems who were recruited through a primary care center in the province of Barcelona (Spain). Positive mental health was assessed by means of the Positive Mental Health Questionnaire (Lluch, 1999). Results: Levels of PMH differed, either on the global scale or on specific factors, in relation to the following variables: age: global PMH scores decreased with age (r=-0.129; p=0.038); b) gender: men scored higher on F1 (t=2.203; p=0.028) and F4 (t=3.182; p=0.002), while women scored higher on F2 (t -3.086; p=0.002) and F6 (t=-2.744; p=0.007); c) number of health conditions: the fewer the number of health problems the higher the PMH score on F5 (r=-0.146; p=0.019); d) daily medication: polymedication patients had lower PMH scores, both globally and on various factors; e) use of analgesics: occasional use of painkillers was associated with higher PMH scores on F1 (t=-2.811; p=0.006). There were no significant differences in global PMH scores according to the type of chronic health condition. The only significant difference in the analysis by factors was that patients with hypertension obtained lower PMH scores on the factor Autonomy (t=2.165; p=0.032). Conclusions: Most people with chronic physical health problems have medium or high levels of PMH. The variables that adversely affect PMH are old age, polypharmacy and frequent consumption of analgesics. The type of health problem does not influence the levels of PMH. Much more extensive studies with samples without chronic pathology are now required in order to be able to draw more robust conclusions.

Robust Estimates of the Negative Binomial Model

We consider robust parametric procedures for univariate discrete distributions, focusing on the negative binomial model. The procedures are based on three steps: ?First, a very robust, but possibly inefficient, estimate of the model parameters is computed. ?Second, this initial model is used to identify outliers, which are then removed from the sample. ?Third, a corrected maximum likelihood estimator is computed with the remaining observations. The final estimate inherits the breakdown point (bdp) of the initial one and its efficiency can be significantly higher. Analogous procedures were proposed in [1], [2], [5] for the continuous case. A comparison of the asymptotic bias of various estimates under point contamination points out the minimum Neyman's chi-squared disparity estimate as a good choice for the initial step. Various minimum disparity estimators were explored by Lindsay [4], who showed that the minimum Neyman's chi-squared estimate has a 50% bdp under point contamination; in addition, it is asymptotically fully efficient at the model. However, the finite sample efficiency of this estimate under the uncontaminated negative binomial model is usually much lower than 100% and the bias can be strong. We show that its performance can then be greatly improved using the three step procedure outlined above. In addition, we compare the final estimate with the procedure described in

Reliable computation of robust response tori on the verge of breakdown

We prove the existence and local uniqueness of invariant tori on the verge of breakdown for two systems: the quasi-periodically driven logistic map and the quasi-periodically forced standard map. These systems exemplify two scenarios: the Heagy-Hammel route for the creation of strange non- chaotic attractors and the nonsmooth bifurcation of saddle invariant tori. Our proofs are computer- assisted and are based on a tailored version of the Newton-Kantorovich theorem. The proofs cannot be performed using classical perturbation theory because the two scenarios are very far from the perturbative regime, and fundamental hypotheses such as reducibility or hyperbolicity either do not hold or are very close to failing. Our proofs are based on a reliable computation of the invariant tori and a careful study of their dynamical properties, leading to the rigorous validation of the numerical results with our novel computational techniques.

On the robust measurement of inflectional diversity

Lexical diversity measures are notoriously sensitive to variations of sample size and recent approaches to this issue typically involve the computation of the average variety of lexical units in random subsamples of fixed size. This methodology has been further extended to measures of inflectional diversity such as the average number of wordforms per lexeme, also known as the mean size of paradigm (MSP) index. In this contribution we argue that, while random sampling can indeed be used to increase the robustness of inflectional diversity measures, using a fixed subsample size is only justified under the hypothesis that the corpora that we compare have the same degree of lexematic diversity. In the more general case where they may have differing degrees of lexematic diversity, a more sophisticated strategy can and should be adopted. A novel approach to the measurement of inflectional diversity is proposed, aiming to cope not only with variations of sample size, but also with variations of lexematic diversity. The robustness of this new method is empirically assessed and the results show that while there is still room for improvement, the proposed methodology considerably attenuates the impact of lexematic diversity discrepancies on the measurement of inflectional diversity.