HF spectrum activity prediction model based on HMM for cognitive radio applications

Although most of the research on Cognitive Radio is focused on communication bands above the HF upper limit (30 MHz), Cognitive Radio principles can also be applied to HF communications to make use of the extremely scarce spectrum more efficiently. In this work we consider legacy users as primary users since these users transmit without resorting to any smart procedure, and our stations using the HFDVL (HF Data+Voice Link) architecture as secondary users. Our goal is to enhance an efficient use of the HF band by detecting the presence of uncoordinated primary users and avoiding collisions with them while transmitting in different HF channels using our broad-band HF transceiver. A model of the primary user activity dynamics in the HF band is developed in this work to make short-term predictions of the sojourn time of a primary user in the band and avoid collisions. It is based on Hidden Markov Models (HMM) which are a powerful tool for modelling stochastic random processes and are trained with real measurements of the 14 MHz band. By using the proposed HMM based model, the prediction model achieves an average 10.3% prediction error rate with one minute-long channel knowledge but it can be reduced when this knowledge is extended: with the previous 8 min knowledge, an average 5.8% prediction error rate is achieved. These results suggest that the resulting activity model for the HF band could actually be used to predict primary users activity and included in a future HF cognitive radio based station.

Artificial metaplasticity prediction model for cognitive rehabilitation outcome in acquired brain injury patients

Objective The main purpose of this research is the novel use of artificial metaplasticity on multilayer perceptron (AMMLP) as a data mining tool for prediction the outcome of patients with acquired brain injury (ABI) after cognitive rehabilitation. The final goal aims at increasing knowledge in the field of rehabilitation theory based on cognitive affectation. Methods and materials The data set used in this study contains records belonging to 123 ABI patients with moderate to severe cognitive affectation (according to Glasgow Coma Scale) that underwent rehabilitation at Institut Guttmann Neurorehabilitation Hospital (IG) using the tele-rehabilitation platform PREVIRNEC©. The variables included in the analysis comprise the neuropsychological initial evaluation of the patient (cognitive affectation profile), the results of the rehabilitation tasks performed by the patient in PREVIRNEC© and the outcome of the patient after a 3–5 months treatment. To achieve the treatment outcome prediction, we apply and compare three different data mining techniques: the AMMLP model, a backpropagation neural network (BPNN) and a C4.5 decision tree. Results The prediction performance of the models was measured by ten-fold cross validation and several architectures were tested. The results obtained by the AMMLP model are clearly superior, with an average predictive performance of 91.56%. BPNN and C4.5 models have a prediction average accuracy of 80.18% and 89.91% respectively. The best single AMMLP model provided a specificity of 92.38%, a sensitivity of 91.76% and a prediction accuracy of 92.07%. Conclusions The proposed prediction model presented in this study allows to increase the knowledge about the contributing factors of an ABI patient recovery and to estimate treatment efficacy in individual patients. The ability to predict treatment outcomes may provide new insights toward improving effectiveness and creating personalized therapeutic interventions based on clinical evidence.

A neuronal model of a global workspace in effortful cognitive tasks

A minimal hypothesis is proposed concerning the brain processes underlying effortful tasks. It distinguishes two main computational spaces: a unique global workspace composed of distributed and heavily interconnected neurons with long-range axons, and a set of specialized and modular perceptual, motor, memory, evaluative, and attentional processors. Workspace neurons are mobilized in effortful tasks for which the specialized processors do not suffice. They selectively mobilize or suppress, through descending connections, the contribution of specific processor neurons. In the course of task performance, workspace neurons become spontaneously coactivated, forming discrete though variable spatio-temporal patterns subject to modulation by vigilance signals and to selection by reward signals. A computer simulation of the Stroop task shows workspace activation to increase during acquisition of a novel task, effortful execution, and after errors. We outline predictions for spatio-temporal activation patterns during brain imaging, particularly about the contribution of dorsolateral prefrontal cortex and anterior cingulate to the workspace.

A structural model of cognitive-motivational variables as explanatory factors of academic achievement in Spanish Language and Mathematics

In recent years, several explanatory models have been developed which attempt to analyse the predictive worth of various factors in relation to academic achievement, as well as the direct and indirect effects that they produce. The aim of this study was to examine a structural model incorporating various cognitive and motivational variables which influence student achievement in the two basic core skills in the Spanish curriculum: Spanish Language and Mathematics. These variables included differential aptitudes, specific self-concept, goal orientations, effort and learning strategies. The sample comprised 341 Spanish students in their first year of Compulsory Secondary Education. Various tests and questionnaires were used to assess each student, and Structural Equation Modelling (SEM) was employed to study the relationships in the initial model. The proposed model obtained a satisfactory fit for the two subjects studied, and all the relationships hypothesised were significant. The variable with the most explanatory power regarding academic achievement was mathematical and verbal aptitude. Also notable was the direct influence of specific self-concept on achievement, goal-orientation and effort, as was the mediatory effect that effort and learning strategies had between academic goals and final achievement.

The hardware design of a cognitive model demonstrator /

"Supported in part by Contract No. U.S. AEC(11-1)1469."

An integrated cognitive model of panic disorder: The role of positive and negative cognitions

One reason for the neglect of the role of positive factors in cognitive-behavioural therapy (CBT) may relate to a failure to develop cognitive models that integrate positive and negative cognitions. Bandura [Psychol. Rev. 84 (1977) 191; Anxiety Res. 1 (1988) 77] proposed that self-efficacy beliefs mediate a range of emotional and behavioural outcomes. However, in panic disorder, cognitively based research to date has largely focused on catastrophic misinterpretation of bodily sensations. Although a number of studies support each of the predictions associated with the account of panic disorder that is based on the role of negative cognitions, a review of the literature indicated that a cognitively based explanation of the disorder may be considerably strengthened by inclusion of positive cognitions that emphasize control or coping. Evidence to support an Integrated Cognitive Model (ICM) of panic disorder was examined and the theoretical implications of this model were discussed in terms of both schema change and compensatory skills accounts of change processes in CBT. (C) 2004 Elsevier Ltd. All rights reserved.

A cognitive model of binge drinking: The influence of alcohol expectancies and drinking refusal self-efficacy

While binge drinking-episodic or irregular consumption of excessive amounts of alcohol-is recognised as a serious problem affecting our youth, to date there has been a lack of psychological theory and thus theoretically driven research into this problem. The current paper develops a cognitive model using the key constructs of alcohol expectancies (AEs) and drinking refusal self-efficacy (DRSE) to explain the acquisition and maintenance of binge drinking. It is suggested that the four combinations of the AE and DRSE can explain the four drinking styles. These are normal/social drinkers, binge drinkers, regular heavy drinkers, and problem drinkers or alcoholics. Since AE and DRSE are cognitive constructs and therefore modifiable, the cognitive model can thus facilitate the design of intervention and-prevention strategies for binge drinking. (C) 2003 Elsevier Ltd. All rights reserved.

Binge drinking in university students: A test of the cognitive model

The aim of this study was to test the cognitive model [Addict. Behav. 29 (2004) 159] of binge drinking in university students. In Study 1, 202 participants completed the Drinking Expectancy Questionnaire (DEQ), the Drinking Refusal Self-Efficacy Questionnaire (DRSEQ), and the Khavari Alcohol Test (KAT). The results showed that both alcohol expectancies (AEs) and drinking refusal self-efficacy (DRSE) are needed to discriminate between binge, social, and heavy drinkers. In general, binge drinkers tend to have higher AEs than social drinkers, and have slightly lower DRSE. However, young social and binge drinkers can only be discriminated on the basis of their AEs. One hundred and fourteen students were recruited for the second study, to predict which individuals would engage in binge drinking during a 4-week self-monitoring period. Over 80% of predicted binge drinkers binged at least once during the monitoring period. These two studies confirmed the cognitive model of binge drinking, and thus, hold implications for the prevention of binge drinking among adolescents and young adults. (C) 2004 Elsevier Ltd. All rights reserved.

Cognitive deficits associated with cancer: A model of subjective and objective outcomes

Cancer and its treatment can affect many different aspects of quality of life. As a construct measured subjectively, quality of life shows an inconsistent relationship with objective outcome measures. That is, sometimes subjective and objective outcomes correspond with each other and sometimes they show little or no relationship. In this article, we propose a model for the relationship between subjective and objective outcomes using the example of cognitive function in people with cancer. The model and the research findings on which it is based help demonstrate that, in some circumstances, subjective measures of cognitive function correlate more strongly with psychosocial variables such as appraisal, coping, and emotions than with objective cognitive function. The model may provide a useful framework for research and clinical practice in quality of life for people with cancer.

Study of the integrated cognitive model of depression among Latin-Americans

Objective: The objective of the present study is to test the validity of the integrated cognitive model (ICM) of depression proposed by Kwon and Oei with a Latin-American sample. The ICM of depression postulates that the interaction between negative life events with dysfunctional attitudes increases the frequency of negative automatic thoughts, which in turns affects the depressive symptomatology of a person. This model was developed for Western Europeans such as Americans and Australians and the validity of this model has not been tested on Latin-Americans. Method: Participants were 101 Latin-American migrants living permanently in Brisbane, including people from Chile, El Salvador, Nicaragua, Argentina and Guatemala. Participants completed the Beck Depression Inventory, the Dysfunctional Attitudes Scale, the Automatic Thoughts Questionnaire and the Life Events Inventory. Alternative or competing models of depression were examined, including the alternative aetiologies model, the linear mediational model and the symptom model. Results: Six models were tested and the results of the structural equation modelling analysis indicated that the symptom model only fits the Latin-American data. Conclusions: Results show that in the Latin-American sample depression symptoms can have an impact on negative cognitions. This finding adds to growing evidence in the literature that the relationship between cognitions and depression is bidirectional, rather than unidirectional from cognitions to symptoms.

Safety behaviors and dysfunctional beliefs about sleep: Testing a cognitive model of the maintenance of insomnia

Objective: Our aim was to determine if insomnia severity, dysfunctional beliefs about sleep, and depression predicted sleep-related safety behaviors. Method: Standard sleep-related measures (such as the Insomnia Severity Index; the Dysfunctional Beliefs About Sleep scale; the Depression, Anxiety, and Stress Scale; and the Sleep-Related Behaviors Questionnaire) were administered. Additionally, 14 days of sleep diary (Pittsburg Sleep Diary) data and actual use of sleep-related behaviors were collected. Results: Regression analysis revealed that dysfunctional beliefs about sleep predicted sleep-related safety behaviors. Insomnia severity did not predict sleep-related safety behaviors. Depression accounted for the greatest amount of unique variance in the prediction of safety behaviors, followed by dysfunctional beliefs. Exploratory analysis revealed that participants with higher levels of depression used more sleep-related behaviors and reported greater dysfunctional beliefs about their sleep. Conclusion: The findings underlie the significant influence that dysfunctional beliefs have on individuals' behaviors. Moreover, the results suggest that depression may need to be considered as an explicit component of cognitive-behavioral models of insomnia. (c) 2006 Elsevier Inc. All rights reserved.

Document retrieval based on a cognitive model of dialogue

Owing to the rise in the volume of literature, problems arise in the retrieval of required information. Various retrieval strategies have been proposed, but most of that are not flexible enough for their users. Specifically, most of these systems assume that users know exactly what they are looking for before approaching the system, and that users are able to precisely express their information needs according to l aid- down specifications. There has, however, been described a retrieval program THOMAS which aims at satisfying incompletely- defined user needs through a man- machine dialogue which does not require any rigid queries. Unlike most systems, Thomas attempts to satisfy the user's needs from a model which it builds of the user's area of interest. This model is a subset of the program's "world model" - a database in the form of a network where the nodes represent concepts since various concepts have various degrees of similarities and associations, this thesis contends that instead of models which assume equal levels of similarities between concepts, the links between the concepts should have values assigned to them to indicate the degree of similarity between the concepts. Furthermore, the world model of the system should be structured such that concepts which are related to one another be clustered together, so that a user- interaction would involve only the relevant clusters rather than the entire database such clusters being determined by the system, not the user. This thesis also attempts to link the design work with the current notion in psychology centred on the use of the computer to simulate human cognitive processes. In this case, an attempt has been made to model a dialogue between two people - the information seeker and the information expert. The system, called Thomas-II, has been implemented and found to require less effort from the user than Thomas.