Chow–Liu trees are sufficient predictive models for reproducing key features of functional networks of periictal EEG time-series

Seizure freedom in patients suffering from pharmacoresistant epilepsies is still not achieved in 20–30% of all cases. Hence, current therapies need to be improved, based on a more complete understanding of ictogenesis. In this respect, the analysis of functional networks derived from intracranial electroencephalographic (iEEG) data has recently become a standard tool. Functional networks however are purely descriptive models and thus are conceptually unable to predict fundamental features of iEEG time-series, e.g., in the context of therapeutical brain stimulation. In this paper we present some first steps towards overcoming the limitations of functional network analysis, by showing that its results are implied by a simple predictive model of time-sliced iEEG time-series. More specifically, we learn distinct graphical models (so called Chow–Liu (CL) trees) as models for the spatial dependencies between iEEG signals. Bayesian inference is then applied to the CL trees, allowing for an analytic derivation/prediction of functional networks, based on thresholding of the absolute value Pearson correlation coefficient (CC) matrix. Using various measures, the thus obtained networks are then compared to those which were derived in the classical way from the empirical CC-matrix. In the high threshold limit we find (a) an excellent agreement between the two networks and (b) key features of periictal networks as they have previously been reported in the literature. Apart from functional networks, both matrices are also compared element-wise, showing that the CL approach leads to a sparse representation, by setting small correlations to values close to zero while preserving the larger ones. Overall, this paper shows the validity of CL-trees as simple, spatially predictive models for periictal iEEG data. Moreover, we suggest straightforward generalizations of the CL-approach for modeling also the temporal features of iEEG signals.

Kawasaki syndrome: Cluster analysis of incident cases presenting to a pediatric tertiary care hospital in Texas from January 1, 2005 to December 31, 2009

Background: Despite almost 40 years of research into the etiology of Kawasaki Syndrome (KS), there is little research published on spatial and temporal clustering of KS cases. Previous analysis has found significant spatial and temporal clustering of cases, therefore cluster analyses were performed to substantiate these findings and provide insight into incident KS cases discharged from a pediatric tertiary care hospital. Identifying clusters from a single institution would allow for prospective analysis of risk factors and potential exposures for further insight into KS etiology. ^ Methods: A retrospective study was carried out to examine the epidemiology and distribution of patients presenting to Texas Children’s Hospital in Houston, Texas, with a diagnosis of Acute Febrile Mucocutaneous Lymph Node Syndrome (MCLS) upon discharge from January 1, 2005 to December 31, 2009. Spatial, temporal, and space-time cluster analyses were performed using the Bernoulli model with case and control event data. ^ Results: 397 of 102,761 total patients admitted to Texas Children’s Hospital had a principal or secondary diagnosis of Acute Febrile MCLS upon over the 5 year period. Demographic data for KS cases remained consistent with known disease epidemiology. Spatial, temporal, and space-time analyses of clustering using the Bernoulli model demonstrated no statistically significant clusters. ^ Discussion: Despite previous findings of spatial-temporal clustering of KS cases, there were no significant clusters of KS cases discharged from a single institution. This implicates the need for an expanded approach to conducting spatial-temporal cluster analysis and KS surveillance given the limitations of evaluating data from a single institution.^

Distributed Fault Diagnosis Using Bayesian Reasoning in MAGNETO

Many of the emerging telecom services make use of Outer Edge Networks, in particular Home Area Networks. The configuration and maintenance of such services may not be under full control of the telecom operator which still needs to guarantee the service quality experienced by the consumer. Diagnosing service faults in these scenarios becomes especially difficult since there may be not full visibility between different domains. This paper describes the fault diagnosis solution developed in the MAGNETO project, based on the application of Bayesian Inference to deal with the uncertainty. It also takes advantage of a distributed framework to deploy diagnosis components in the different domains and network elements involved, spanning both the telecom operator and the Outer Edge networks. In addition, MAGNETO features self-learning capabilities to automatically improve diagnosis knowledge over time and a partition mechanism that allows breaking down the overall diagnosis knowledge into smaller subsets. The MAGNETO solution has been prototyped and adapted to a particular outer edge scenario, and has been further validated on a real testbed. Evaluation of the results shows the potential of our approach to deal with fault management of outer edge networks.

Probabilistic reasoning with a bayesian DNA device based on strand displacement

We present a computing model based on the DNA strand displacement technique which performs Bayesian inference. The model will take single stranded DNA as input data, representing the presence or absence of a specific molecular signal (evidence). The program logic encodes the prior probability of a disease and the conditional probability of a signal given the disease playing with a set of different DNA complexes and their ratios. When the input and program molecules interact, they release a different pair of single stranded DNA species whose relative proportion represents the application of Bayes? Law: the conditional probability of the disease given the signal. The models presented in this paper can empower the application of probabilistic reasoning in genetic diagnosis in vitro.

A multi-agent system with distributed bayesian reasoning for network fault diagnosis

In this paper, an innovative approach to perform distributed Bayesian inference using a multi-agent architecture is presented. The final goal is dealing with uncertainty in network diagnosis, but the solution can be of applied in other fields. The validation testbed has been a P2P streaming video service. An assessment of the work is presented, in order to show its advantages when it is compared with traditional manual processes and other previous systems.

Desarrollo y aplicaciones de radares de alta resolución en bandas milimétricas

Las bandas de las denominadas ondas milimétricas y submilimétricas están situadas en la región del espectro entre las microondas y el infrarrojo. La banda de milimétricas se sitúa entre 30 y 300 GHz, considerada normalmente como la banda EHF (Extremely High Frequency). El margen de frecuencias entre 300 y 3000 GHz es conocido como la banda de ondas submilimétricas o de terahercios (THz). Sin embargo, no toda la comunidad científica está de acuerdo acerca de las frecuencias que limitan la banda de THz. De hecho, 100 GHz y 10 THz son considerados comúnmente como los límites inferior y superior de dicha banda, respectivamente. Hasta hace relativamente pocos años, la banda de THz sólo había sido explotada para aplicaciones en los campos de la espectroscopía y la radioastronomía. Los avances tecnológicos en la electrónica de microondas y la óptica lastraron el desarrollo de la banda de THz. Sin embargo, investigaciones recientes han demostrado las ventajas asociadas a operar en estas longitudes de onda, lo que ha aumentado el interés y los esfuerzos dedicados a la tecnología de THz. A pesar de que han surgido un gran número de aplicaciones, una de las más prometedoras está en el campo de la vigilancia y la seguridad. Esta tesis está dedicada al desarrollo de radares de onda continua y frecuencia modulada (CW-LFM) de alta resolución en la banda de milimétricas, más concretamente, en las ventanas de atenuación situadas en 100 y 300 GHz. Trabajar en estas bandas de frecuencia presenta beneficios tales como la capacidad de las ondas de atravesar ciertos materiales como la ropa o el papel, opacos en el rango visible, y la posibilidad de usar grandes anchos de banda, obteniéndose así elevadas resoluciones en distancia. Los anchos de banda de 9 y 27 GHz seleccionados para los sistemas de 100 y 300 GHz, respectivamente, proporcionan resoluciones en distancia alrededor y por debajo del cm. Por otro lado, las aplicaciones objetivo se centran en la adquisición de imágenes a corto alcance. En el caso del prototipo a 300 GHz, su diseño se ha orientado a aplicaciones de detección a distancia en escenarios de vigilancia y seguridad. La naturaleza no ionizante de esta radiación supone una ventaja frente a las alternativas tradicionalmente usadas tales como los sistemas de rayos X. La presente tesis se centra en el proceso de diseño, implementación y caracterización de ambos sistemas así como de la validación de su funcionamiento. Se ha elegido una solución basada en componentes electrónicos, y no ópticos, debido a su alta fiabilidad, volumen reducido y amplia disponibilidad de componentes comerciales. Durante el proceso de diseño e implementación, se han tenido en cuenta varias directrices tales como la minimización del coste y la versatilidad de los sistemas desarrollados para hacer posible su aplicación para múltiples propósitos. Ambos sistemas se han utilizado en diferentes pruebas experimentales, obteniendo resultados satisfactorios. Aunque son sólo ejemplos dentro del amplio rango de posibles aplicaciones, la adquisición de imágenes ISAR de modelos de blancos a escala para detección automática así como la obtención de datos micro-Range/micro- Doppler para el análisis de patrones humanos han validado el funcionamiento del sistema a 100 GHz. Por otro lado, varios ejemplos de imágenes 3D obtenidas a 300 GHz han demostrado las capacidades del sistema para su uso en tareas de seguridad y detección a distancia. ABSTRACT The millimeter- and submillimeter-wave bands are the regions of the spectrum between the microwaves and the infrared (IR). The millimeter-wave band covers the range of the spectrum from 30 to 300 GHz, which is usually considered as the extremely high frequency (EHF) band. The range of frequencies between 300 and 3000 GHz is known as the submillimeter-wave or terahertz (THz) band. Nevertheless, the boundaries of the THz band are not accepted by the whole research community. In fact, 100 GHz and 10 THz are often considered by some authors as the lower and upper limit of this band, respectively. Until recently, the THz band had not been exploited for practical applications, with the exception of minor uses in the fields of spectroscopy and radio astronomy. The advancements on microwave electronics and optical technology left the well-known THz gap undeveloped. However, recent research has unveiled the advantages of working at these frequencies, which has motivated the increase in research effort devoted to THz technology. Even though the range of upcoming applications is wide, the most promising ones are in the field of security and surveillance. Particularly, this Ph.D. thesis deals with the development of high resolution continuouswave linear-frequency modulated (CW-LFM) radars in the millimeter-wave band, namely, in the attenuation windows located at 100 and 300 GHz. Working at these wavelengths presents several benefits such as the ability of radiation to penetrate certain materials, visibly opaque, and the great availability of bandwidth at these frequencies, which leads to high range resolution. The selected bandwidths of 9 and 27 GHz for these systems at 100 and 300 GHz, respectively, result in cm and sub-cm range resolution. On the other hand, the intended applications are in the field of short-range imaging. In particular, the design of the 300-GHz prototype is oriented to standoff detection for security and surveillance scenarios. The non-ionizing nature of this radiation allows safety concerns to be alleviated, in clear contrast to other traditional alternatives such as X-rays systems. This thesis is focused on the design, implementation and characterization process of both systems as well as the experimental assessment of their performances. An electronic approach has been selected instead of an optical solution so as to take advantage of its high reliability, reduced volume and the availability of commercial components. Through the whole design and implementation process, several guidelines such as low cost and hardware versatility have been also kept in mind. Taking advantage of that versatility, different applications can be carried out with the same hardware concept. Both radar systems have been used in several experimental trials with satisfactory results. Despite being mere examples within the wide range of fields of application, ISAR imaging of scaled model targets for automatic target recognition and micro-Range/micro-Doppler analysis of human patterns have validated the system performance at 100 GHz. In addition, 3D imaging examples at 300 GHz demonstrate the radar system’s capabilities for standoff detection and security tasks.

B2DI a bayesian BDI agent model with causal belief updating based on MSBN

In this paper, we introduce B2DI model that extends BDI model to perform Bayesian inference under uncertainty. For scalability and flexibility purposes, Multiply Sectioned Bayesian Network (MSBN) technology has been selected and adapted to BDI agent reasoning. A belief update mechanism has been defined for agents, whose belief models are connected by public shared beliefs, and the certainty of these beliefs is updated based on MSBN. The classical BDI agent architecture has been extended in order to manage uncertainty using Bayesian reasoning. The resulting extended model, so-called B2DI, proposes a new control loop. The proposed B2DI model has been evaluated in a network fault diagnosis scenario. The evaluation has compared this model with two previously developed agent models. The evaluation has been carried out with a real testbed diagnosis scenario using JADEX. As a result, the proposed model exhibits significant improvements in the cost and time required to carry out a reliable diagnosis.

MultiPARTES: Multicore Virtualization for Mixed-Criticality Systems

Modern embedded applications typically integrate a multitude of functionalities with potentially different criticality levels into a single system. Without appropriate preconditions, the integration of mixed-criticality subsystems can lead to a significant and potentially unacceptable increase of engineering and certification costs. A promising solution is to incorporate mechanisms that establish multiple partitions with strict temporal and spatial separation between the individual partitions. In this approach, subsystems with different levels of criticality can be placed in different partitions and can be verified and validated in isolation. The MultiPARTES FP7 project aims at supporting mixed- criticality integration for embedded systems based on virtualization techniques for heterogeneous multicore processors. A major outcome of the project is the MultiPARTES XtratuM, an open source hypervisor designed as a generic virtualization layer for heterogeneous multicore. MultiPARTES evaluates the developed technology through selected use cases from the offshore wind power, space, visual surveillance, and automotive domains. The impact of MultiPARTES on the targeted domains will be also discussed. In a number of ongoing research initiatives (e.g., RECOMP, ARAMIS, MultiPARTES, CERTAINTY) mixed-criticality integration is considered in multicore processors. Key challenges are the combination of software virtualization and hardware segregation and the extension of partitioning mechanisms to jointly address significant non-functional requirements (e.g., time, energy and power budgets, adaptivity, reliability, safety, security, volume, weight, etc.) along with development and certification methodology.

Computational models of cortical visual processing.

The visual responses of neurons in the cerebral cortex were first adequately characterized in the 1960s by D. H. Hubel and T. N. Wiesel [(1962) J. Physiol. (London) 160, 106-154; (1968) J. Physiol. (London) 195, 215-243] using qualitative analyses based on simple geometric visual targets. Over the past 30 years, it has become common to consider the properties of these neurons by attempting to make formal descriptions of these transformations they execute on the visual image. Most such models have their roots in linear-systems approaches pioneered in the retina by C. Enroth-Cugell and J. R. Robson [(1966) J. Physiol. (London) 187, 517-552], but it is clear that purely linear models of cortical neurons are inadequate. We present two related models: one designed to account for the responses of simple cells in primary visual cortex (V1) and one designed to account for the responses of pattern direction selective cells in MT (or V5), an extrastriate visual area thought to be involved in the analysis of visual motion. These models share a common structure that operates in the same way on different kinds of input, and instantiate the widely held view that computational strategies are similar throughout the cerebral cortex. Implementations of these models for Macintosh microcomputers are available and can be used to explore the models' properties.

O endossamento de celebridades na propaganda sob a ótica do Neuromarketing: um estudo sobre a influência de uma celebridade no processo de atenção visual

O presente estudo buscou entender a influência da utilização da celebridade Gisele Bundchen em anúncios de propaganda no comportamento do consumidor por meio de uma das técnicas de Neuromarketing: o eye tracking. Sendo assim, esta pesquisa objetivou analisar se é realmente importante a presença da celebridade em propagandas de anúncio impresso analisada sob o ponto de vista do Neuromarketing por meio da análise da atenção visual ao estímulo \'celebridade\'. Para a verificação dos objetivos, das hipóteses e da proposição advindas destes objetivos, foi empregada uma metodologia em que se buscou avaliar a atenção visual dos consumidores acerca do estímulo \'celebridade\' em relação aos demais estímulos presentes nos anúncios impressos como a logomarca, nome ou símbolo que representa a marca; o produto; e outras pessoas não famosas. Essa avaliação foi realizada por meio da técnica de Neuromarketing que utiliza o equipamento de eye tracking. Assim, os participantes foram divididos em três grupos (um que avaliou os anúncios das seis marcas com a celebridade; o outro que avaliou os anúncios destas mesmas marcas com a presença de pessoas não famosas e um último grupo que avaliou os anúncios das marcas sem a presença de pessoas). No final do foi aplicado um questionário para confirmação de alguns dados e para análise em relação à lembrança da marca. Os resultados, no geral, demonstraram que, de alguma forma, os participantes prestaram atenção na celebridade considerada na pesquisa (o que foi evidenciado, principalmente, pelos mapas de calor apresentados). Quando as celebridades foram comparadas às pessoas não famosas, em alguns casos (com a confirmação de algumas hipóteses), foi evidenciada a importância da presença da celebridade; porém, em outros casos, houve mais destaque para a presença da pessoa não famosa. Na pesquisa ficou evidente, também, que a presença de pessoas (sendo elas celebridade ou não) pode atrapalhar no processo de atenção para a marca e o produto e que, quando não se utilizou pessoas, houve mais atenção dos participantes para estes outros estímulos.

Constrained self-organizing feature map to preserve feature extraction topology

In many classification problems, it is necessary to consider the specific location of an n-dimensional space from which features have been calculated. For example, considering the location of features extracted from specific areas of a two-dimensional space, as an image, could improve the understanding of a scene for a video surveillance system. In the same way, the same features extracted from different locations could mean different actions for a 3D HCI system. In this paper, we present a self-organizing feature map able to preserve the topology of locations of an n-dimensional space in which the vector of features have been extracted. The main contribution is to implicitly preserving the topology of the original space because considering the locations of the extracted features and their topology could ease the solution to certain problems. Specifically, the paper proposes the n-dimensional constrained self-organizing map preserving the input topology (nD-SOM-PINT). Features in adjacent areas of the n-dimensional space, used to extract the feature vectors, are explicitly in adjacent areas of the nD-SOM-PINT constraining the neural network structure and learning. As a study case, the neural network has been instantiate to represent and classify features as trajectories extracted from a sequence of images into a high level of semantic understanding. Experiments have been thoroughly carried out using the CAVIAR datasets (Corridor, Frontal and Inria) taken into account the global behaviour of an individual in order to validate the ability to preserve the topology of the two-dimensional space to obtain high-performance classification for trajectory classification in contrast of non-considering the location of features. Moreover, a brief example has been included to focus on validate the nD-SOM-PINT proposal in other domain than the individual trajectory. Results confirm the high accuracy of the nD-SOM-PINT outperforming previous methods aimed to classify the same datasets.

Investigating the potential magnetic origin of wind variability in OB stars

In this thesis, the origin of large-scale structures in hot star winds, believed to be responsible for the presence of discrete absorption components (DACs) in the absorption troughs of ultraviolet resonance lines, is constrained using both observations and numerical simulations. These structures are understood as arising from bright regions on the stellar surface, although their physical cause remains unknown. First, we use high quality circular spectropolarimetric observations of 13 well-studied OB stars to evaluate the potential role of dipolar magnetic fields in producing DACs. We perform longitudinal field measurements and place limits on the field strength using Bayesian inference, assuming that it is dipolar. No magnetic field was detected within this sample. The derived constraints statistically refute any significant dynamical influence from a magnetic dipole on the wind for all of these stars, ruling out such fields as a cause for DACs. Second, we perform numerical simulations using bright spots constrained by broadband optical photometric observations. We calculate hydrodynamical wind models using three sets of spot sizes and strengths. Co-rotating interaction regions are yielded in each model, and radiative transfer shows that the properties of the variations in the UV resonance lines synthesized from these models are consistent with those found in observed UV spectra, establishing the first consistent link between UV spectroscopic line profile variability and photometric variations and thus supporting the bright spot paradigm (BSP). Finally, we develop and apply a phenomenological model to quantify the measurable effects co-rotating bright spots would have on broadband optical photometry and on the profiles of photopheric lines in optical spectra. This model can be used to evaluate the existence of these spots, and, in the event of their detection, characterize them. Furthermore, a tentative spot evolution model is presented. A preliminary analysis of its output, compared to the observed photometric variations of xi Persei, suggests the possible existence of “active longitudes” on the surface of this star. Future work will expand the range of observational diagnostics that can be interpreted within the BSP, and link phenomenology (bright spots) to physical processes (magnetic spots or non-radial pulsations).

Approach to challenging behaviour: a family affair

Over the past 30 years, research in the area of applied behaviour. analysis has led to a rich knowledge and understanding of the variables that influence human behaviour. This understanding and knowledge has given rise to a range of assessment and intervention techniques that have been applied to individuals with challenging behaviour. Interventions have produced changes in the severity and frequency of behaviours such as self-injury, aggression, and property destruction, card have also led to the acquisition of desired behaviours. While behaviour change has been achieved, families have expressed a desire for positive behaviour support approaches that adopt a family,focus. Research and development of support frameworks that emphasise the interrelatedness of family members, and the child with a disability as part of his or her family, have gained prominence in the family systems literature. The present paper reviews some of the behaviourally based research in this area. Through the use of a case illustration, the authors discuss the links between behavioural support and family-centred support systems for children with developmental disabilities. Theoretical and practical implications are considered and areas for future research are highlighted.

Thirty-year recovery trend in the once depleted Hawaiian green sea turtle stock

The green sea turtle is one of the long-lived species that comprise the charismatic marine megafauna. The green turtle has a long history of human exploitation with some stocks extinct. Here we report on a 30-year study of the nesting abundance of the green turtle stock endemic to the Hawaiian Archipelago. We show that there has been a substantial long-term increase in abundance of this once seriously depleted stock following cessation of harvesting since the 1970s. This population increase has occurred in a far shorter period of time than previously thought possible. There was also a distinct 3-4 year periodicity in annual nesting abundance that might be a function of regional environmental stochasticity that synchronises breeding behaviour throughout the Archipelago. This is one of the few reliable long-term population abundance time series for a large long-lived marine species, which are needed for gaining insights into the recovery process of long-lived marine species and long-term ecological processes. (C) 2003 Elsevier Ltd. All rights reserved.

Extinction times for a birth-death process with two phases

Many populations have a negative impact on their habitat or upon other species in the environment if their numbers become too large. For this reason they are often subjected to some form of control. One common control regime is the reduction regime: when the population reaches a certain threshold it is controlled (for example culled) until it falls below a lower predefined level. The natural model for such a controlled population is a birth-death process with two phases, the phase determining which of two distinct sets of birth and death rates governs the process. We present formulae for the probability of extinction and the expected time to extinction, and discuss several applications. (c) 2006 Elsevier Inc. All rights reserved.