998 resultados para Cognitive Architecture


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Cognitive Radio principles can be applied to HF communications to make a more efficient use of the extremely scarce spectrum. In this contribution we focus on analyzing the usage of the available channels done by the legacy users, which are regarded as primary users since they are allowed to transmit without resorting any smart procedure, and consider the possibilities for our stations -over the HFDVL (HF Data+Voice Link) architecture- to participate 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. It is based on Hidden Markov Models (HMM) which are a powerful tool for modelling stochastic random processes, and is trained with real measurements from the 14 MHz band.

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The progressive ageing of population has turned the mild cognitive impairment (MCI) into a prevalent disease suffered by elderly. Consequently, the spatial disorientation has become a significant problem for older people and their caregivers. The ambient-assisted living applications are offering location-based services for empowering elderly to go outside and encouraging a greater independence. Therefore, this paper describes the design and technical evaluation of a location-awareness service enabler aimed at supporting and managing probable wandering situations of a person with MCI. Through the presence capabilities of the IP multimedia subsystem (IMS) architecture, the service will alert patient's contacts if a hazardous situation is detected depending on his location. Furthermore, information about the older person's security areas has been included in the user profile managed by IMS. In doing so, the service enabler introduced contribute to “context-awareness” paradigm allowing the adaptation and personalization of services depending on user's context and specific conditions or preferences.

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Collaborative working with the aid of computers is increasing rapidly due to the widespread use of computer networks, geographic mobility of people, and small powerful personal computers. For the past ten years research has been conducted into this use of computing technology from a wide variety of perspectives and for a wide range of uses. This thesis adds to that previous work by examining the area of collaborative writing amongst groups of people. The research brings together a number of disciplines, namely sociology for examining group dynamics, psychology for understanding individual writing and learning processes, and computer science for database, networking, and programming theory. The project initially looks at groups and how they form, communicate, and work together, progressing on to look at writing and the cognitive processes it entails for both composition and retrieval. The thesis then details a set of issues which need to be addressed in a collaborative writing system. These issues are then followed by developing a model for collaborative writing, detailing an iterative process of co-ordination, writing and annotation, consolidation, and negotiation, based on a structured but extensible document model. Implementation issues for a collaborative application are then described, along with various methods of overcoming them. Finally the design and implementation of a collaborative writing system, named Collaborwriter, is described in detail, which concludes with some preliminary results from initial user trials and testing.

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This article presents the principal results of the doctoral thesis “Semantic-oriented Architecture and Models for Personalized and Adaptive Access to the Knowledge in Multimedia Digital Library” by Desislava Ivanova Paneva-Marinova (Institute of Mathematics and Informatics), successfully defended before the Specialised Academic Council for Informatics and Mathematical Modelling on 27 October, 2008.

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OBJECTIVE: To test common genetic variants for association with seasonality (seasonal changes in mood and behavior) and to investigate whether there are shared genetic risk factors between psychiatric disorders and seasonality. METHOD: Genome-wide association studies (GWASs) were conducted in Australian (between 1988 and 1990 and between 2010 and 2013) and Amish (between May 2010 and December 2011) samples in whom the Seasonal Pattern Assessment Questionnaire (SPAQ) had been administered, and the results were meta-analyzed in a total sample of 4,156 individuals. Genetic risk scores based on results from prior large GWAS studies of bipolar disorder, major depressive disorder (MDD), and schizophrenia were calculated to test for overlap in risk between psychiatric disorders and seasonality. RESULTS: The most significant association was with rs11825064 (P = 1.7 × 10⁻⁶, β = 0.64, standard error = 0.13), an intergenic single nucleotide polymorphism (SNP) found on chromosome 11. The evidence for overlap in risk factors was strongest for schizophrenia and seasonality, with the schizophrenia genetic profile scores explaining 3% of the variance in log-transformed global seasonality scores. Bipolar disorder genetic profile scores were also associated with seasonality, although at much weaker levels (minimum P value = 3.4 × 10⁻³), and no evidence for overlap in risk was detected between MDD and seasonality. CONCLUSIONS: Common SNPs of large effect most likely do not exist for seasonality in the populations examined. As expected, there were overlapping genetic risk factors for bipolar disorder (but not MDD) with seasonality. Unexpectedly, the risk for schizophrenia and seasonality had the largest overlap, an unprecedented finding that requires replication in other populations and has potential clinical implications considering overlapping cognitive deficits in seasonal affective disorders and schizophrenia.

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The use of Cyber Physical Systems (CPS) to optimise industrial energy systems is an approach which has the potential to positively impact on manufacturing sector energy efficiency. The need to obtain data to facilitate the implementation of a CPS in an industrial energy system is however a complex task which is often implemented in a non-standardised way. The use of the 5C CPS architecture has the potential to standardise this approach. This paper describes a case study where data from a Combined Heat and Power (CHP) system located in a large manufacturing company was fused with grid electricity and gas models as well as a maintenance cost model using the 5C architecture with a view to making effective decisions on its cost efficient operation. A control change implemented based on the cognitive analysis enabled via the 5C architecture implementation has resulted in energy cost savings of over €7400 over a four-month period, with energy cost savings of over €150,000 projected once the 5C architecture is extended into the production environment.

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This thesis explores the methods based on the free energy principle and active inference for modelling cognition. Active inference is an emerging framework for designing intelligent agents where psychological processes are cast in terms of Bayesian inference. Here, I appeal to it to test the design of a set of cognitive architectures, via simulation. These architectures are defined in terms of generative models where an agent executes a task under the assumption that all cognitive processes aspire to the same objective: the minimization of variational free energy. Chapter 1 introduces the free energy principle and its assumptions about self-organizing systems. Chapter 2 describes how from the mechanics of self-organization can emerge a minimal form of cognition able to achieve autopoiesis. In chapter 3 I present the method of how I formalize generative models for action and perception. The architectures proposed allow providing a more biologically plausible account of more complex cognitive processing that entails deep temporal features. I then present three simulation studies that aim to show different aspects of cognition, their associated behavior and the underlying neural dynamics. In chapter 4, the first study proposes an architecture that represents the visuomotor system for the encoding of actions during action observation, understanding and imitation. In chapter 5, the generative model is extended and is lesioned to simulate brain damage and neuropsychological patterns observed in apraxic patients. In chapter 6, the third study proposes an architecture for cognitive control and the modulation of attention for action selection. At last, I argue how active inference can provide a formal account of information processing in the brain and how the adaptive capabilities of the simulated agents are a mere consequence of the architecture of the generative models. Cognitive processing, then, becomes an emergent property of the minimization of variational free energy.

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This study aimed to evaluate long-term atrophy in contralateral hippocampal volume after surgery for unilateral MTLE, as well as the cognitive outcome for patients submitted to either selective transsylvian amygdalohippocampectomy (SelAH) or anterior temporal lobe resection (ATL). We performed a longitudinal study of 47 patients with MRI signs of unilateral hippocampal sclerosis (23 patients with right-sided hippocampal sclerosis) who underwent surgical treatment for MTLE. They underwent preoperative/postoperative high-resolution MRI as well as neuropsychological assessment for memory and estimated IQ. To investigate possible changes in the contralateral hippocampus of patients, we included 28 controls who underwent two MRIs at long-term intervals. The volumetry using preoperative MRI showed significant hippocampal atrophy ipsilateral to the side of surgery when compared with controls (p<0.0001) but no differences in contralateral hippocampal volumes. The mean postoperative follow-up was 8.7 years (± 2.5 SD; median=8.0). Our patients were classified as Engel I (80%), Engel II (18.2%), and Engel III (1.8%). We observed a small but significant reduction in the contralateral hippocampus of patients but no volume changes in controls. Most of the patients presented small declines in both estimated IQ and memory, which were more pronounced in patients with left TLE and in those with persistent seizures. Different surgical approaches did not impose differences in seizure control or in cognitive outcome. We observed small declines in cognitive scores with most of these patients, which were worse in patients with left-sided resection and in those who continued to suffer from postoperative seizures. We also demonstrated that manual volumetry can reveal a reduction in volume in the contralateral hippocampus, although this change was mild and could not be detected by visual analysis. These new findings suggest that dynamic processes continue to act after the removal of the hippocampus, and further studies with larger groups may help in understanding the underlying mechanisms.

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this study aimed to investigate the cognitive and behavioral profiles, as well as the psychiatric symptoms and disorders in children with three different genetic syndromes with similar sociocultural and socioeconomic backgrounds. thirty-four children aged 6 to 16 years, with Williams-Beuren syndrome (n=10), Prader-Willi syndrome (n=11), and Fragile X syndrome (n=13) from the outpatient clinics of Child Psychiatry and Medical Genetics Department were cognitively assessed through the Wechsler Intelligence Scale for Children (WISC-III). Afterwards, a full-scale intelligence quotient (IQ), verbal IQ, performance IQ, standard subtest scores, as well as frequency of psychiatric symptoms and disorders were compared among the three syndromes. significant differences were found among the syndromes concerning verbal IQ and verbal and performance subtests. Post-hoc analysis demonstrated that vocabulary and comprehension subtest scores were significantly higher in Williams-Beuren syndrome in comparison with Prader-Willi and Fragile X syndromes, and block design and object assembly scores were significantly higher in Prader-Willi syndrome compared with Williams-Beuren and Fragile X syndromes. Additionally, there were significant differences between the syndromes concerning behavioral features and psychiatric symptoms. The Prader-Willi syndrome group presented a higher frequency of hyperphagia and self-injurious behaviors. The Fragile X syndrome group showed a higher frequency of social interaction deficits; such difference nearly reached statistical significance. the three genetic syndromes exhibited distinctive cognitive, behavioral, and psychiatric patterns.

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A comparison of the oral health of elderly people with and without a cognitive handicap was assessed. The cognitive condition, the indices of decayed, missing, filled teeth (DMFT), decayed, filled roots (DFR), the need for dental treatment, the presence of plaque (P), calculus (C), the community periodontal index (CPI), the rate of periodontal attachment loss (PAL), edentulism, prosthetic use and the need for prosthetics were evaluated in a complex probabilistic sample by conglomerates of the elderly (65-74 years). PASW(r) 17.0 was used for the statistical analyses with correction for the design effect, applying the Mann Whitney and chi-square test with 95% reliability. A total of 736 elderly individuals were interviewed and examined. Those with cognitive impairment had higher average DMFT, DFR and lower average healthy sextant CPI, a lower prevalence of sextants without plaque/calculus, use of prosthetics and higher prevalence of edentulism and need for prosthetics. Elderly individuals with a cognitive handicap had poorer oral health.

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Ecological science contributes to solving a broad range of environmental problems. However, lack of ecological literacy in practice often limits application of this knowledge. In this paper, we highlight a critical but often overlooked demand on ecological literacy: to enable professionals of various careers to apply scientific knowledge when faced with environmental problems. Current university courses on ecology often fail to persuade students that ecological science provides important tools for environmental problem solving. We propose problem-based learning to improve the understanding of ecological science and its usefulness for real-world environmental issues that professionals in careers as diverse as engineering, public health, architecture, social sciences, or management will address. Courses should set clear learning objectives for cognitive skills they expect students to acquire. Thus, professionals in different fields will be enabled to improve environmental decision-making processes and to participate effectively in multidisciplinary work groups charged with tackling environmental issues.

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The pathological mechanisms underlying cognitive dysfunction in multiple sclerosis (MS) are not yet fully understood and, in addition to demyelinating lesions and gray-matter atrophy, subclinical disease activity may play a role. To evaluate the contribution of asymptomatic gadolinium-enhancing lesions to cognitive dysfunction along with gray-matter damage and callosal atrophy in relapsing-remitting MS (RRMS) patients. Forty-two treated RRMS and 30 controls were evaluated. MRI (3T) variables of interest were brain white-matter and cortical lesion load, cortical and deep gray-matter volumes, corpus callosum volume and presence of gadolinium-enhancing lesions. Outcome variables included EDSS, MS Functional Composite (MSFC) subtests and the Brief Repeatable Battery of Neuropsychological tests. Cognitive dysfunction was classified as deficits in two or more cognitive subtests. Multivariate regression analyses assessed the contribution of MRI metrics to outcomes. Patients with cognitive impairment (45.2%) had more cortical lesions and lower gray-matter and callosal volumes. Patients with subclinical MRI activity (15%) had worse cognitive performance. Clinical disability on MSFC was mainly associated with putaminal atrophy. The main independent predictors for cognitive deficits were high burden of cortical lesions and number of gadolinium-enhancing lesions. Cognitive dysfunction was especially related to high burden of cortical lesions and subclinical disease activity. Cognitive studies in MS should look over subclinical disease activity as a potential contributor to cognitive impairment.

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OBJECTIVE: Despite the relevance of irritability emotions to the treatment, prognosis and classification of psychiatric disorders, the neurobiological basis of this emotional state has been rarely investigated to date. We assessed the brain circuitry underlying personal script-driven irritability in healthy subjects (n = 11) using functional magnetic resonance imaging. METHOD: Blood oxygen level-dependent signal changes were recorded during auditory presentation of personal scripts of irritability in contrast to scripts of happiness or neutral emotional content. Self-rated emotional measurements and skin conductance recordings were also obtained. Images were acquired using a 1,5T magnetic resonance scanner. Brain activation maps were constructed from individual images, and between-condition differences in the mean power of experimental response were identified by using cluster-wise nonparametric tests. RESULTS: Compared to neutral scripts, increased blood oxygen level-dependent signal during irritability scripts was detected in the left subgenual anterior cingulate cortex, and in the left medial, anterolateral and posterolateral dorsal prefrontal cortex (cluster-wise p-value < 0.05). While the involvement of the subgenual cingulate and dorsal anterolateral prefrontal cortices was unique to the irritability state, increased blood oxygen level-dependent signal in dorsomedial and dorsal posterolateral prefrontal regions were also present during happiness induction. CONCLUSION: Irritability induction is associated with functional changes in a limited set of brain regions previously implicated in the mediation of emotional states. Changes in prefrontal and cingulate areas may be related to effortful cognitive control aspects that gain salience during the emergence of irritability.

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This paper proposes an architecture for machining process and production monitoring to be applied in machine tools with open Computer numerical control (CNC). A brief description of the advantages of using open CNC for machining process and production monitoring is presented with an emphasis on the CNC architecture using a personal computer (PC)-based human-machine interface. The proposed architecture uses the CNC data and sensors to gather information about the machining process and production. It allows the development of different levels of monitoring systems with mininium investment, minimum need for sensor installation, and low intrusiveness to the process. Successful examples of the utilization of this architecture in a laboratory environment are briefly described. As a Conclusion, it is shown that a wide range of monitoring solutions can be implemented in production processes using the proposed architecture.