We propose a statistical method for modeling the non-Poisson variability of spike trains observed in a wide range of brain regions. Central to our approach is the assumption that the variance and the mean of interspike intervals are related by a power function characterized by two parameters: the scale factor and exponent. It is shown that this single assumption allows the variability of spike ...

Attractive train schedules are quite important for the success of public rail transport. We consider schedules which are repeated after some xed time period. Periodicity is a well accepted, convenient attribute of all major railroad systems. Since trains share the public railroad network, we have to handle many connicting demands. Increasing competition from transportation alternatives as well ...

This paper presented a new height-resolved view of global dust transport based on 2007-2010 Atrain observations. First, a new dust identification methodology was developed to improve optically thin dust layer detection. Second a new dust partition methodology was developed and applied to CALIPSO lidar measurements to derive dust partitions in external mixed aerosols. These new approaches allow ...

Thomas Kreuz, Daniel Chicharro, Conor Houghton, Ralph G. Andrzejak, and Florian Mormann Institute for Complex Systems, CNR, Sesto Fiorentino, Italy; Center for Neuroscience and Cognitive Systems@UniTn, Italian Institute of Technology, Rovereto (TN), Italy; Department of Computer Science, University of Bristol, Bristol, United Kingdom; Department of Information and Communication Technologies, Un...

Accurate positioning of vehicles plays an important role in autonomous driving. In our previous research on landmark-based positioning, poles were extracted both from reference data and online sensor data, which were then matched to improve the positioning accuracy of the vehicles. However, there are environments which contain only a limited number of poles. 3D feature points are one of the pro...

Railway scheduling is a complex task of rail operators that involves the generation of a conflict-free train timetable. This paper presents a discrete-event simulation-based optimization approach for solving the train timetabling problem to minimize total weighted unplanned stop time in a hybrid single and double track railway networks. The designed simulation model is used as a platform for ge...

Although GNSS/IMU integration has been studied for decades, an efficient estimator of their integration has remained a challenge. In the statistical approaches, the observation model of sensors and distribution of data must be known beforehand. This paper proposes a deep learning based approach to integrate GPS and reduced IMU information. In contrast to statistical approaches, our approach lea...

In neurophysiological studies with awake non-human primates (NHP), it is typically necessary to train the animals over a prolonged period of time on a behavioral paradigm before the actual data collection takes place. Rhesus monkeys (Macaca mulatta) are the most widely used primate animal models in system neuroscience. Inspired by existing joystick- or touch-screen-based systems designed for a ...

ABSTRACTBackground: Preterm birth, if not actively managed with developmental supportive care, can significantly contribute to neurodevelopmental compromise. Use of appropriate positioning aids helps with mimicking the intrauterine environment and facilitating neuromuscular development. Herein, we aimed to determine the effectiveness of snuggle up positioning aids on clinical outcomes of preterm (

<p>WiFi indoor positioning researches have received much attention from researchers recently. In this research, we focus on studying the performance of systems that utilize our new proposed ensemble machine learning model. Our model uses several models for normal data training and position prediction, then it verification together with its' prediction errors trained as input to train an i...