Abstract: We study the data from a passive traffic measurement representing a 30 hour IP traffic trace from a Finnish operator’s GPRS/UMTS network. Of specific interest is the variability of the Round Trip Times (RTTs) of the TCP flows in the network. The RTTs are analysed at both microand macroscopic level. The microscopic level involves detailed analysis of individual flows and we are able to...

Statistical mimicking issues involving reaction time measures are introduced and discussed in this article. Often, discussions of mimicking have concerned the question of the serial vs. parallel processing of inputs to the cognitive system. We will demonstrate that there are several alternative structures that mimic various existing models in the literature. In particular, single process models...

Customizable software systems allow users to derive configurations by selecting features. Building a performance model to understand the tradeoff between performance and feature selection is important to be able to derive a desired configuration. A challenge is to predict performance accurately when features interact. Another is that, in practice, we can often measure only few configurations as...

Many of the chemical reactions that take place within a living cell are irreversible. Due to evolutionary pressures, the number of allowable reactions within these systems are highly constrained and thus the resulting metabolic networks display considerable asymmetry. In this paper, we explore possible evolutionary factors pertaining to the reduced symmetry observed in these networks, and demon...

Learning to categorize objects involves learning which sources of variability are meaningful and which should be ignored or generalized. In this light, theories and models of category learning can be viewed as accounts of how people capture and represent meaningful variation. Similarity-based models, such as prototype and exemplar models, cannot correctly predict that humans classify a stimulus...

In inter-subject registration, one often lacks a good model of the transformation variability to choose the optimal regularization. Some works attempt to model the variability in a statistical way, but the re-introduction in a registration algorithm is not easy. In [1], we interpreted the elastic energy as the distance of the Green-St Venant strain tensor to the identity. By changing the Euclid...

Voice and speech parameters for a single speaker vary widely over different contexts, in particular in situations in which speakers are affected by stress or emotion or in which speech styles are used strategically. This high degree of intra-speaker variability presents a major challenge for speaker verification systems. Based on a large-scale study in which different kinds of affective states ...

4 , the ChemCam team and the MSL team. Introduction: The huge spectra collection that ChemCam instrument [Wiens, 2012] has acquired since Curiosity landed at Gale crater contains a wealth of informations that are hard to decipher in details because of the rather high number of phenomena that infuence these spectra. However, the reproducibility of these spectra in similar conditions looks quite ...

h THE CONSTANT EVOLUTION of electronic systems has been fueled by the continuous and tremendous progress of silicon technology manufacturing. Since 1960, when the first MOS transistor was manufactured with dimensions around 50 m, process technology has been constantly enhancing until the current 22-nm MOS technology. Every two years a new process generation roughly doubles the device density, f...

We focus on the problem of shape variability modeling in statistical pattern recognition. We present a nonlinear statistical model invariant to affine transformations. This model is learned on an ordinate set of points. The concept of relations between model components is also taken in account. This model is used to find curves and points partially occulted in the image. We present its applicat...