No abstract

The brain is one of the largest and most complex organs in the human body and EEG is a noninvasive electrophysiological monitoring method that is used to record the electrical activity of the brain. Lately, the functional connectivity in human brain has been regarded and studied as a complex network using EEG signals. This means that the brain is studied as a connected system where nodes, or units, represent different specialized brain regions and links, or connections, represent communication pathways between the nodes. Graph theory and theory of complex networks provide a variety of measures, methods, and tools that can be useful to efficiently model, analyze, and study EEG networks. This article is addressed to computer scientists who wish to be acquainted and deal with the study of EEG data and also to neuroscientists who would like to become familiar with graph theoretic approaches and tools to analyze EEG data.

No abstract

This study explored the use of wearable sensor technology to investigate autonomic function in children with autism spectrum disorder (ASD) and Rett syndrome (RTT). We aimed to identify autonomic biomarkers that can correctly differentiate females with ASD and Rett Syndrome using an innovative methodology that applies machine learning approaches. Our findings suggest that we can predict (95%) the status of ASD/Rett. We conclude that physiological biomarkers may be able to assist in the differentiation between patients with RTT and ASD and could allow the development of timely therapeutic strategies.

Object oriented dependable server applications often rely on fault tolerance schemes, which are comprised of different replication policies for the constituent objects (composite replication schemes). This paper introduces a simulation-based evaluation approach for quantifying the tradeoffs between fault-tolerance overhead and fault tolerance effectiveness in composite replication schemes. Compared to other evaluation approaches: (a) we do not use the well-known reliability blocks based simulation, but a hybrid reliability and system's traffic simulation and (b) we make a clear distinction between the measures used for the fault-affected service response times from those used for the fault-unaffected ones. The first mentioned feature allows taking into account additional concerns other than fault tolerance, like for example load balancing and multithreading. The second feature renders the proposed approach suitable for design studies that aim to determine either optimal replication properties for the constituent objects or Quality of Service (QoS) guarantees for the perceived service response times. We obtain results for a case system model, based on different assumptions on what happens when server-objects fail (loss scenarios). The presented results give insight in the design of composite method request-retry schemes with appropriate request timeouts.