Advances of high-order interactions in the human brain: Applications in aging and neurodegeneration.

82 p.The human brain generates a large repertoire of spatio-temporal patterns, which supporta wide variety of motor, cognitive, and behavioral functions. The most acceptedhypothesis in modern neuroscience is that each of these representations is encoded indifferent brain networks. From MRI, networks can be defined anatomically (¿structuralconnectivity¿-SC) or functionally (¿functional connectivity¿-FC). Interestingly, while SCis by definition pairwise (white matter fibers project from one region to another), FC isnot. In this thesis we have focused on the study of high-order interactions (HOI) that occur in functional networks, beyond the existing statistical relationships in pairs of regions.When evaluating the interacting n-plets, from triplets to order n, a novel type of statistical interdependencies appear, namely the synergistic and redundant interactions,which are inaccessible when evaluating interacting pairs. The study of these HOI inthe human brain in aging and neurodegeneration is the purpose of this thesis.Biocruces Bizkai

Probabilistic Graphical Modelling for Software Product Lines: A Frameweork for Modeling and Reasoning under Uncertainty

This work provides a holistic investigation into the realm of feature modeling within software product lines. The work presented identifies limitations and challenges within the current feature modeling approaches. Those limitations include, but not limited to, the dearth of satisfactory cognitive presentation, inconveniency in scalable systems, inflexibility in adapting changes, nonexistence of predictability of models behavior, as well as the lack of probabilistic quantification of model’s implications and decision support for reasoning under uncertainty. The work in this thesis addresses these challenges by proposing a series of solutions. The first solution is the construction of a Bayesian Belief Feature Model, which is a novel modeling approach capable of quantifying the uncertainty measures in model parameters by a means of incorporating probabilistic modeling with a conventional modeling approach. The Bayesian Belief feature model presents a new enhanced feature modeling approach in terms of truth quantification and visual expressiveness. The second solution takes into consideration the unclear support for the reasoning under the uncertainty process, and the challenging constraint satisfaction problem in software product lines. This has been done through the development of a mathematical reasoner, which was designed to satisfy the model constraints by considering probability weight for all involved parameters and quantify the actual implications of the problem constraints. The developed Uncertain Constraint Satisfaction Problem approach has been tested and validated through a set of designated experiments. Profoundly stating, the main contributions of this thesis include the following: • Develop a framework for probabilistic graphical modeling to build the purported Bayesian belief feature model. • Extend the model to enhance visual expressiveness throughout the integration of colour degree variation; in which the colour varies with respect to the predefined probabilistic weights. • Enhance the constraints satisfaction problem by the uncertainty measuring of the parameters truth assumption. • Validate the developed approach against different experimental settings to determine its functionality and performance

Statistics of gradient directions in natural images.

Interest in finding statistical regularities in natural images has been growing since the advent of information theory and the advancement of the efficient coding hypothesis that the human visual system is optimised to encode natural visual stimuli. In this thesis, a statistical analysis of gradient directions in an ensemble of natural images is reported. Information-theoretic measures have been used to compute the amount of dependency which exists between triples of gradient directions at separate image locations. Control experiments are performed on other image classes: phase randomized natural images, whitened natural images, and Gaussian noise images. The main results show that for an ensemble of natural images the average amount of de pendency between two and three gradient directions is the same as for an ensemble of phase randomized natural images. This result does not extend to i) the amount dependency between gradient magnitudes, ii) gradient directions at high gradient magnitude locations, or iii) individual natural images. Furthermore, no significant synergetic dependencies are found between triples of gradient directions in an ensemble natural images a synergetic dependency is an increase in dependency between a pair of gradient directions given the interaction of a third gradient direction. Additional experiments are performed to establish both the generality and specificity of the main results by studying the gradient direction dependencies of ensembles of noise (random phases) images with varying power law power spectra. The results of the additional experiments indicate that, for ensembles of images with varying power law power spectra, the amount of dependency between two and three gradient directions is determined by the ensemble's mean power spectrum rather than the phase spectrum. A framework is also presented for future work and preliminary results are provided for the dependency between second order derivative measurements (shape index) for up to 9-point configurations

A model for putting connectivism into practice in a classroom environment

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies ManagementTechnology in education, as in most pillars of society, represents a trend for the new era. Often referred to as Smart Education, the integration of technology into learning environments with the goal of enhancing the experience for students and teachers has been of growing interest to learning institutions. The emergence of a heterodox theory of learning, connectivism, has come to prioritize the incessant search for new and accurate information and, consequently, the capacity of the learner to build knowledge through the connection of nodes within the chaos of contradictory opinions. Being connectivism associated with the reality of an e-learning context, it remains challenging to adapt it into a setting of presential university classes. The model developed in this paper is a proposition of how to fill this gap, hence answering the question of how to put connectivism into practice in a campus environment. The framework, which combines the students’ self-research, and online interaction with their peers through social media platforms, culminating in physical classroom discussions, reflects the connectivism principles and is beneficial for the majority of students. Unlike most connectivism-inspired class dynamics, here, the professor’s role is critical, with the responsibility of moderation and capacity to assess whether the students have been successful in building knowledge through their connections. Although the aim of the study is to apply connectivism principles in a physical campus, the relevance of work-oriented social media platforms in this model is undeniable

Forum Session at the First International Conference on Service Oriented Computing (ICSOC03)

The First International Conference on Service Oriented Computing (ICSOC) was held in Trento, December 15-18, 2003. The focus of the conference ---Service Oriented Computing (SOC)--- is the new emerging paradigm for distributed computing and e-business processing that has evolved from object-oriented and component computing to enable building agile networks of collaborating business applications distributed within and across organizational boundaries. Of the 181 papers submitted to the ICSOC conference, 10 were selected for the forum session which took place on December the 16th, 2003. The papers were chosen based on their technical quality, originality, relevance to SOC and for their nature of being best suited for a poster presentation or a demonstration. This technical report contains the 10 papers presented during the forum session at the ICSOC conference. In particular, the last two papers in the report ere submitted as industrial papers

Safety assessment of next generation nuclear systems: methodology development and case studies on fission and fusion devices

L'abstract è presente nell'allegato / the abstract is in the attachmen