Collaborative Spectrum Sensing from Sparse Observations in Cognitive Radio Networks

Spectrum sensing, which aims at detecting spectrum holes, is the precondition for the implementation of cognitive radio (CR). Collaborative spectrum sensing among the cognitive radio nodes is expected to improve the ability of checking complete spectrum usage. Due to hardware limitations, each cognitive radio node can only sense a relatively narrow band of radio spectrum. Consequently, the available channel sensing information is far from being sufficient for precisely recognizing the wide range of unoccupied channels. Aiming at breaking this bottleneck, we propose to apply matrix completion and joint sparsity recovery to reduce sensing and transmitting requirements and improve sensing results. Specifically, equipped with a frequency selective filter, each cognitive radio node senses linear combinations of multiple channel information and reports them to the fusion center, where occupied channels are then decoded from the reports by using novel matrix completion and joint sparsity recovery algorithms. As a result, the number of reports sent from the CRs to the fusion center is significantly reduced. We propose two decoding approaches, one based on matrix completion and the other based on joint sparsity recovery, both of which allow exact recovery from incomplete reports. The numerical results validate the effectiveness and robustness of our approaches. In particular, in small-scale networks, the matrix completion approach achieves exact channel detection with a number of samples no more than 50% of the number of channels in the network, while joint sparsity recovery achieves similar performance in large-scale networks.Comment: 12 pages, 11 figure

Cue-Triggered Addiction and Natural Recovery

In this paper we propose a model of natural recovery, a widespread yet unexplained aspect of addictive behavior, starting from the recent theory developed by Bernheim and Rangel (2004). While the Bernheim and Rangel model generates many distinctive patterns of addiction, it does not explicitly consider pathways to natural recovery. Based on insights from neurosciences, we introduce an ”implicit cognitive appraisal” process depending on past experiences as well as on future expected consequences of addictive consumption. Such function affects the individual in two ways: it erodes the payoff from use as the decision maker grows older and it increases the cognitive control competing with the hedonic impulses to use, thus reducing the probability of making mistakes. While we do recognize the importance of allowing for cue-triggered mistakes in individual decision making, our model recovers an important role for cognitive processes, such as subjective cost-benefit evaluations, in explaining natural recovery.Addiction models, natural recovery, behavioral economics,cognitive policy, neuroscience.

Protocol for the Reconstructing Consciousness and Cognition (ReCCognition) Study

Important scientific and clinical questions persist about general anesthesia despite the ubiquitous clinical use of anesthetic drugs in humans since their discovery. For example, it is not known how the brain reconstitutes consciousness and cognition after the profound functional perturbation of the anesthetized state, nor has a specific pattern of functional recovery been characterized. To date, there has been a lack of detailed investigation into rates of recovery and the potential orderly return of attention, sensorimotor function, memory, reasoning and logic, abstract thinking, and processing speed. Moreover, whether such neurobehavioral functions display an invariant sequence of return across individuals is similarly unknown. To address these questions, we designed a study of healthy volunteers undergoing general anesthesia with electroencephalography and serial testing of cognitive functions (NCT01911195). The aims of this study are to characterize the temporal patterns of neurobehavioral recovery over the first several hours following termination of a deep inhaled isoflurane general anesthetic and to identify common patterns of cognitive function recovery. Additionally, we will conduct spectral analysis and reconstruct functional networks from electroencephalographic data to identify any neural correlates (e.g., connectivity patterns, graph-theoretical variables) of cognitive recovery after the perturbation of general anesthesia. To accomplish these objectives, we will enroll a total of 60 consenting adults aged 20–40 across the three participating sites. Half of the study subjects will receive general anesthesia slowly titrated to loss of consciousness (LOC) with an intravenous infusion of propofol and thereafter be maintained for 3 h with 1.3 age adjusted minimum alveolar concentration of isoflurane, while the other half of subjects serves as awake controls to gauge effects of repeated neurobehavioral testing, spontaneous fatigue and endogenous rest-activity patterns

The Intentional Use of Service Recovery Strategies to Influence Consumer Emotion, Cognition and Behaviour

Service recovery strategies have been identified as a critical factor in the success of. service organizations. This study develops a conceptual frame work to investigate how specific service recovery strategies influence the emotional, cognitive and negative behavioural responses of . consumers., as well as how emotion and cognition influence negative behavior. Understanding the impact of specific service recovery strategies will allow service providers' to more deliberately and intentionally engage in strategies that result in positive organizational outcomes. This study was conducted using a 2 x 2 between-subjects quasi-experimental design. The results suggest that service recovery has a significant impact on emotion, cognition and negative behavior. Similarly, satisfaction, negative emotion and positive emotion all influence negative behavior but distributive justice has no effect

SRLG inference in OSPF for improved reconvergence after failures

The ECODE FP7 project researches cognitive routing functions in future networks. We demonstrate machine learning augmented OSPF routing which infers SRLGs from network failure history. Inferred SRLGs are used to improve OSPF convergence and recovery times during subsequent (multiple) network failures

Validation of the cognitive recovery assessments with the Postoperative Quality of Recovery Scale in patients with low-baseline cognition

Patients with pre-surgery cognitive impairment cannot currently be assessed for cognitive recovery after surgery using the Postoperative Quality of Recovery Scale (PostopQRS),as they would mathematically be scored as recovered. The group nonetheless represent a frail cohort at high risk of recovering poorly. We aimed to validate a novel method to score cognitive recovery in patients with low baseline cognition, using the number of low-score tests rather than their numerical values. Face validity was demonstrated in 86 participants in whom both PostopQRS and an 11-item neuropsychological battery were performed. The PostopQRS agreed with neuropsychological categorization of low versus normal cognition 74% of the time, with all but 5 incorrectly coded participants deviating by only 1 neurocognitive test. Cognitive recovery over time was comparable for groups with differing baseline cognitive function, irrespective of whether PostopQRS or neuropsychological methods were used. Discriminant validation was demonstrated in a post hoc analysis of the Steroids in Cardiac Surgery (SIRS) substudy by allocating groups to normal (n=246) or low baseline cognition (n=231) stratified by cognitive recovery on day 1. Recovery was similar for participants with low and normal baseline cognition. Postoperative length of stay was longer in patients with failed cognitive recovery whether they had normal (10.4±10.0 vs. 8.0±5.9 days, P=0.02) or low baseline cognition (12.0±11.1 vs. 8.2±4.7 days, P<0.01). Overall quality of recovery, as well as cognitive, emotive, and physiological recovery in those who recovered was independent of baseline cognition. The modified scoring method for the PostopQRS cognitive domain therefore demonstrates acceptable face and discriminant validity

Recovery self-efficacy and intention as predictors of running or jogging behavior: a cross-lagged panel analysis over a two-year period

Objectives: The study investigates whether two kinds of self-efficacy and intention predict regular running or jogging behavior over 2 yr. Maintenance self-efficacy refers to beliefs about one's ability to maintain a behavior, whereas recovery self-efficacy pertains to beliefs about one's ability to resume a behavior after a setback. Design and methods: Longitudinal data from runners (N=139, 80% men) were collected twice with a time gap of 2 yr. Results: Cross-lagged panel analysis revealed that recovery self-efficacy and intention jointly predicted running/jogging behavior 2 yr later, whereas running/jogging behavior did not predict recovery self-efficacy and intention. No effects of maintenance self-efficacy were found. The majority of participants (n=120) experienced at least one 2-week period of decline in running or jogging behavior. Among those who experienced lapses, recovery self-efficacy remained the only significant social-cognitive predictor of behavior. Conclusions: Recovery self-efficacy is a crucial predictor of regular running or jogging behavior over 2 yr