Background: The use of a cell phone when driving has been recognized as a type of distraction worldwide. Addictive tendency to use technology, including cell phone use while driving may be a substantial problem for drivers and increasing risk of accidents. The aim of this study was to evaluate the effect of drivers’ addiction to use a cell phone while driving.  Materials and Methods...

Abstract Urban complex scenarios are the most challenging situations in field of Autonomous Driving (AD). In that sense, an AD pipeline should be tested countless environments and scenarios, escalating cost development time exponentially with a physical approach. this paper we present validation our fully-autonomous driving architecture using NHTSA (National Highway Traffic Safety Administratio...

In this paper we provide efficient robust algorithms for shunting problems concerning the reordering of train cars over a hump. In particular, we study algorithms able to cope with small disruptions, as temporary and local unavailability and/or malfunctioning of key resources that can occur and affect planned operations. To this aim, a definition of robust algorithm is provided. Performances of...

Many sentiment-analysis methods for the classification of reviews use training and test-data based on star ratings provided by reviewers. However, when reading reviews it appears that the reviewers’ ratings do not always give an accurate measure of the sentiment of the review. We performed an annotation study which showed that reader perceptions can also be expressed in ratings in a reliable wa...

Spike train regularity of the noisy neural auditory system model under the influence of two sinusoidal signals with different frequencies is investigated. For the increasing ratio m/n of the input signal frequencies (m, n are natural numbers) the linear growth of the regularity is found at the fixed difference (m - n). It is shown that the spike train regularity in the model is high for harmoni...

Neurons integrate inputs from thousands of afferents. Similarly, some experimental techniques record the pooled activity of large populations of cells. When cells in these populations are correlated, the correlation coefficient between the collective activity of two subpopulations is typically much larger than the correlation coefficient between individual cells: The act of pooling individual c...

Recognition of nonlinearities in the neuronal encoding of repetitive spike trains has generated a number of models to explain this behavior. Here we develop the mathematics and a set of tests for two such models: the leaky integrator and the variable-gamma model. Both of these are nearly sufficient to explain the dynamic behavior of a number of repetitively firing, sensory neurons. Model parame...

We examine the effect of the phase-resetting curve on the transfer of correlated input signals into correlated output spikes in a class of neural models receiving noisy superthreshold stimulation. We use linear-response theory to approximate the spike correlation coefficient in terms of moments of the associated exit time problem and contrast the results for type I vs type II models and across ...

We present a kinetic theory for all-to-all coupled networks of identical, linear, integrate-and-fire, excitatory point neurons in which a fast and a slow excitatory conductance are driven by the same spike train in the presence of synaptic failure. The maximal-entropy principle guides us in deriving a set of three (1+1) -dimensional kinetic moment equations from a Boltzmann-like equation descri...

We develop a method from semiparametric statistics (Cox, 1972) for the purpose of tracking links and connection strengths over time in a neuronal network from spike train data. We consider application of the method as implemented in Masud and Borisyuk (2011), and evaluate its use on data generated independently of the Cox model hypothesis, in particular from a spiking model of Izhikevich in fou...